DDI_SDN_2008_PHC_v01_M_v7.5_A_IPUMS 5th Population and Housing Census IPUMS May 20, 2024 MetadataEditor Version 7.5 October 2024. NEW FEATURES. --Historical data from NAPP project now available from IPUMS-International. --Historical census data from Canada, Denmark, the United Kingdom, Germany, Iceland, Norway, Sweden, and the United States for the period 1703 to 1911 are now available from IPUMS-International. The complete count and sample datasets were previously disseminated by the North Atlantic Population Project (NAPP). Where possible, the data have been integrated into existing IPUMS-International variable coding schema. Some new variables have been created that are available only for these pre-1960 datasets. NAPP data users should note that many NAPP variables are available from IPUMS-International by different names. For a complete list of NAPP variables that have been renamed in IPUMS-Interational, refer to the crosswalk. --Individual country shapefiles for the third-level administrative level of geography are now available for a few IPUMS samples. --New spatially harmonized previous-residence variables at the second administrative level of geography are available for several samples in this data release. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --IPUMS now hosts the Census Mosaic data collection. Census Mosaic identifies, gathers, harmonizes, and distributes surviving historical census microdata from regions of Continental Europe where complete centralized records are not available. The Mosaic project was founded by a consortium of historical social scientists in Europe. Data can be downloaded as static files from the Census Mosaic website. Although the data are not yet integrated fully into IPUMS International, variables have been standardized and harmonized to be roughly compatible with IPUMS coding structures. NEW SAMPLES. --Full-count datasets for Great Britain 1851, 1861, 1871 (Scotland only), 1891, and 1901. --Full-count dataset for Sweden 1910. Denmark (1845, 1880, and 1885) --Labor force surveys from Spain and eight new labor force surveys from Italy added to the series. Newly added countries: Benin, Cote d'Ivoire, Finland, Guatemala, Honduras, Laos, Lesotho, Mauritius, Myanmar, Papua New Guinea, Russia, Slovak Republic, Suriname, Togo, and Zimbabwe New samples for: Bolivia, Cambodia, Cambodia, Chile, Cuba, Cote d'Ivoire, Egypt (1848 and 1868, historical samples), Fiji, Guinea, Ireland, Israel, Italy, Lao PDR, Mexico, Morocco, Nepal, Netherlands, Palestine, Peru, Philippines, Puerto Rico, Rwanda, Senegal, Sierra Leone, South Africa, Switzerland, Uganda, United States, United Kingdom, United States, Vietnam, and Zimbabwe SUPPLEMENTAL DATA. Data from censuses from Benin and Lesotho that record individual fertility and/or mortality events were made available in IPUMS-International. These files can be downloaded and linked to data produced by the extract system. NEW VARIABLES. --IPUMS-International now provides harmonized and year-specific geography variables for all countries including 13 new samples from Dominican Republic, Germany, Indonesia, Israel, Malaysia, Mongolia, Nicaragua, Nigeria, Palestine, Paraguay, Thailand, United Kingdom, and Uruguay. First-level and second-level year specific geography variables are also available for all countries. IPUMS provides corresponding, downloadable GIS boundary files for all harmonized and year specific geography variables. More information about IPUMS geography variables is available here. --IPUMS International now provides spatially harmonized previous-residence variables at the first administrative level of geography. The codes for the spatially harmonized previous-residence variables match the spatially harmonized place of current residence. More information is available here. --IPUMS International provides spatially harmonized previous-residence variables at the first administrative level of geography for all samples; previously available country-specific migration variables at the first administrative level that were not fully harmonized spatially have been phased out. Spatially harmonized previous-residence variables at the second administrative level of geography are available for selected samples. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --IPUMS International now provides spatially harmonized previous-residence variables at the first administrative level of geography for all samples. Spatially harmonized previous-residence variables at the second administrative level of geography are available for several samples in this data release. More information is available here. Users should note that many older migration variables are available by different names. Refer to this table for a crosswalk of old and corresponding new migration variables. --Lower (third) level geography codes and GIS files have been added for Bangladesh, China, Ethiopia, Mali, Rwanda, and Zimbabwe. Some geography codes and labels might have changed for these countries to accommodate the newer lower level geography. --Added more detailed 3-digit industry and occupation variables for China 2000. EDITED SAMPLES. --Revised full-count data for Great Britain 1881 --Revised full-count datasets for Sweden 1890 and 1900. The revision includes the following changes that improve comparability across Sweden datasets: --Revisions to certain ethnicity and work variables (and the underlying source data): ORIGIN, LABFORCE, OCCHISCO, OCRELATE, OCSTATUS. --Revisions to unharmonized source variables: SE1890A_HISCOSE, SE1890A_HISCRELSE, SE1890A_HISCSTATSE, SE1890A_OCCMULTISE, SE1900A_HISCOSE, SE1900A_HISCRELSE, SE1900A_HISCSTATSE, SE1900A_OCCMULTISE. --A new United States 1850 full-count dataset now matches the corresponding dataset distributed by the USA IPUMS data project. The source variable US1850A_0502 (HISTID) provides a linking key to match person records to the USA version of the data. The IPUMS International version of the data contains names, which the USA version cannot distribute. EDITED VARIABLES. An error affecting HHWT for South Africa 2007 was corrected. The existing values were adjusted by a factor of 0.01. AGEMARR was edited to add data for Hungary 1980 and 1990. Harmonized and year-specific geography variables for Brazil and Colombia have been edited to accommodate for the availability of refined municipal boundaries. Users should be aware that codes and labels have changed in all harmonized and year specific geography varaibles for these two countries. Errors affecting BPLSE2 (formerly BPLPARSE) for Sweden 1890 and the underlying source variable were corrected. Several thousand cases were incorrectly coded as 258101000. These cases have been updated with the correct code: 258171000. Harmonized geography variables for Italy, Philippines, Rwanda, and United States have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year specific geography varaibles for these countries. More information about IPUMS geography variables is available here. The codes for the source variable RW2002A_0419 were corrected to include 0 and 8 as possible responses, which were previously identified as 'unknown years' within primary education. Errors affecting EDUCFJ for Fiji 2006 were corrected. A problem with PERWT for Tanzania 2012 was corrected. The previous weights were adjusted to properly reflect population totals. MOMLOC, POPLOC, and PARRULE were updated for the United States 2010 and 2015 samples to include additional information on subfamilies. Prior to this correction, persons above age 17 were not receiving links to their co-resident mothers and fathers. An error affecting codes for the URBAN variable in Egypt 1986 for Cairo, Alexandria, Port-Said, and Suez was corrected. An error in INCEARN affecting Venezuela 2001 was corrected. Earned income in the source variable VE2001A_0440 is interpreted as a monthly amount, thus adjustments previously applied to convert data from daily or weekly income were supressed. All the six Brazil samples in IPUMS International were replaced with higher density samples. An edited version of the Chile 2017 sample was introduced to correct an error in household breaks. Errors affecting codes for GEO1_ZA in South Africa 2011 and ENUTS1 in United Kingdom 1991 were corrected. Harmonized geography variables for Cambodia, Fiji, and Nepal have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography varaibles for these countries. More information about IPUMS geography variables is available here. An error in PERWT affecting Nepal 2001 was corrected. Errors affecting a code in GQ for Brazil 2010 and Indonesia 2010 were corrected. Both census samples now identify 1-person units created by splitting a large household. An error in MARRNUM affecting Indonesia 1976 was corrected. Some codes for GEO1_EG2006 and GEO2_EG2006 were edited. Harmonized geography variables for Bolivia, Cuba, Guinea, Ireland, Morocco, Palestine, Senegal, South Africa, and Uganda have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. An error in INCEARN affecting Brazil 1980 was corrected. An error in EDATTAIN affecting Ireland 1971 and 1981 was corrected. A small proportion of person records in Mexico 1960 were re-classified in MIGRATEP based on information about their current and previous residence. These were previously coded to 'different major administrative unit', even though their place of residence suggests that their last move was within the same major administrative unit. The second-level technician (higher) degrees for Spain 1991, 2001, and 2011 were re-classified into post-secondary technical education in EDATTAIN. An error affecting codes for SEX for Egypt 1848 and 1868 was corrected. The values for male and female had been reversed. A problem with HHWT and PERWT for Canada 2011 was corrected. The previous weights were adjusted to properly reflect population totals. Harmonized geography variables for Cambodia, Lao PDR, Mexico, Peru, Switzerland, Vietnam, Puerto Rico, United Kingdom, and United States have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. Harmonized geography variables for Chile and Sierra Leone have been edited to accommodate new samples. Users should be aware that codes and labels have changed in all harmonized and year-specific geography variables for these countries. More information about IPUMS geography variables is available here. An error affecting codes for COMPUTER for Senegal 2013 was corrected. An error affecting labels available in IND for Peru 1993 was corrected. An error affecting codes for persons previously residing abroad for MIG1_5_BO in Bolivia 2001 and 2012 was corrected. EDUCAR, EDATTAIN, and YRSCHOOL were adjusted in the Argentina samples to incorporate information on completion of education levels in the data harmonization. HHWT and PERWT were calibrated in Kenya 1979 to properly reflect the population distribution by province. In GQ (group quarters status), persons residing in hospitals of all types were reclassified to 'institutional group quarters' from 'other group quarters,' making their treatment consistent with GQTYPE. Errors affecting codes for BPLBJ2 in Benin 1979, 1992, and 2002 were corrected. Errors affecting codes for GEO2_BR1970 in Brazil 1970 were corrected. 5th Population and Housing Census - IPUMS Subset PHC Sudan 2008 (IPUMS Harmonized Subset) SDN_2008_PHC_v01_M_v7.5_A_IPUMS Central Bureau of Statistics IPUMS (c) Copyright 2008, Central Bureau of Statistics and Minnesota Population Center MetadataEditor Central Bureau of Statistics Population and Housing Census [hh/popcen] IPUMS International DOI:10.18128/D020.V7.5 Version 7.5. The datasets contain selected variables from the original census microdata plus harmonized variables from the IPUMS-International database. Demographic Variables -- PERSON Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Fertility and Mortality Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Nativity and Birthplace Variables -- PERSON Utilities Variables -- HOUSEHOLD Work Variables -- PERSON Technical Household Variables -- HOUSEHOLD Geography: IPUMS-I, IPUMS-DHS Variables -- HOUSEHOLD Disability Variables -- PERSON Education Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Migration: Global Variables -- PERSON Group Quarters Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Migration: O-Z Variables -- PERSON Technical Person Variables -- PERSON Technical Household Variables -- HOUSEHOLD Education Variables -- PERSON Demographic Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Dwelling Characteristics Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Technical Person Variables -- PERSON Geography: O-Z Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Household Imputation Flags Variables -- HOUSEHOLD Household Imputation Flags Variables -- HOUSEHOLD Technical Household Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Demographic Variables -- PERSON Nativity and Birthplace Variables -- PERSON Migration: Global Variables -- PERSON Fertility and Mortality Variables -- PERSON Disability Variables -- PERSON Education Variables -- PERSON Work Variables -- PERSON Work: Occupation Variables -- PERSON Work: Industry Variables -- PERSON Person Imputation Flags Variables -- PERSON Person Imputation Flags Variables -- PERSON Technical Person Variables -- PERSON Fertility and Mortality Variables -- PERSON Sudan County Persons and households UNITS IDENTIFIED: - Dwellings: no - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: no UNIT DESCRIPTIONS: - Dwellings: A building is an independent free-standing structure irrespective of its construction material, composed of one or more rooms. - Households: A household consists of a person or a group of persons who live together in the same housing unit or part of it and who consider themselves as one unit in terms of the provision of food and/or other essentials of living for the group. When most of the members of such a group are related by blood (i.e., biologically) the group shall be referred to as a Private Household for the purpose of the census. On the other hand when the group (i.e., household as defined earlier) consists of members who are not related by blood and they are more than 10, they will be considered as Non-Institutional Collective Household. Note that if the group consists of 10 or less members, it should be considered a private household. - Group quarters: An institution is usually a set of premises used to house a large number of people who are not related by blood or marriage but bound together by a common objective or personal interest (e.g., universities, boarding houses, hospitals, army barracks, camps, prisons, hotels, etc.) Residents of Sudan Homeless, regugees, camp residents. Nomadic population is that group of people who rear cattle or livestock and do not stay in specific areas for long periods of time. They live in mobile housing units, usually made of wood, hide, etc. and are continuously moving in search of water and grazing for their animals. Administratively they are affiliated to tribal 'Sheikhs'and 'Farigs' councils. Population and Housing Census [hh/popcen] Additional notes on a sample that is part of this study: Sudan 2008 MICRODATA SOURCE: Central Bureau of Statistics SAMPLE SIZE (person records): 5066530. SAMPLE DESIGN: Long form questionnaire for sedentary households (selected enumeration areas) and a sample of nomad households. Homeless, regugees, camp residents. Nomadic population is that group of people who rear cattle or livestock and do not stay in specific areas for long periods of time. They live in mobile housing units, usually made of wood, hide, etc. and are continuously moving in search of water and grazing for their animals. Administratively they are affiliated to tribal 'Sheikhs'and 'Farigs' councils. Face-to-face [f2f] Two forms: Long Questionnaire (for a sample of areas) and Short Questionnaire (for the rest of the country). The information used here is based on the long form questionnaire. de facto, CENSUS DAY: April 22, 2008 Computed by census agency and should be used for most types of analysis. IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS International are designed to extend this record. Central Bureau of Statistics Steven Ruggles, Lara Cleveland, Rodrigo Lovaton, Sula Sarkar, Matthew Sobek, Derek Burk, Dan Ehrlich, Quinn Heimann, Jane Lee. Integrated Public Use Microdata Series, International: Version 7.5 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.1 [dataset]. Minneapolis, MN: IPUMS, 2024. https://doi.org/10.18128/D020.V7.5 Researchers should also acknowledge the statistical agency that originally produced the data: Sudan, Central Bureau of Statistics. 5th Population and Housing Census The licensing agreement for use of IPUMS International data requires that users supply IPUMS International with the title and full citation for any publications, research reports, or educational materials making use of the data or documentation. Copies of such materials are also gratefully received at ipums@umn.edu. Printed matter should be sent to: IPUMS International Minnesota Population Center University of Minnesota 50 Willey Hall 225 19th Avenue South Minneapolis, MN 55455 An adapted version of the dataset, harmonized for international comparability, is available from IPUMS International (https://international.ipums.org/international/) under the following conditions: IPUMS International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. SDN2008_PHC-H-H Household records 922 152 SDN2008_PHC-P-H Person records 5066530 173 Record type H Household P Person RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. IPUMS Country 032 Argentina 051 Armenia 040 Austria 050 Bangladesh 112 Belarus 204 Benin 068 Bolivia 072 Botswana 076 Brazil 854 Burkina Faso 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 208 Denmark 214 Dominican Republic 218 Ecuador 818 Egypt 222 El Salvador 231 Ethiopia 242 Fiji 246 Finland 250 France 276 Germany 288 Ghana 300 Greece 320 Guatemala 324 Guinea 332 Haiti 340 Honduras 348 Hungary 352 Iceland 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 384 Ivory Coast 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 418 Laos 426 Lesotho 430 Liberia 454 Malawi 458 Malaysia 466 Mali 480 Mauritius 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 104 Myanmar 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 578 Norway 586 Pakistan 275 Palestine 591 Panama 598 Papua New Guinea 600 Paraguay 604 Peru 608 Philippines 616 Poland 620 Portugal 630 Puerto Rico 642 Romania 643 Russia 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 703 Slovak Republic 705 Slovenia 710 South Africa 728 South Sudan 724 Spain 729 Sudan 740 Suriname 752 Sweden 756 Switzerland 834 Tanzania 764 Thailand 768 Togo 780 Trinidad and Tobago 792 Turkey 800 Uganda 804 Ukraine 826 United Kingdom 840 United States 858 Uruguay 862 Venezuela 704 Vietnam 894 Zambia 716 Zimbabwe COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). IPUMS Year 1703 1703 1729 1729 1787 1787 1801 1801 1819 1819 1845 1845 1848 1848 1850 1850 1851 1851 1852 1852 1860 1860 1861 1861 1865 1865 1868 1868 1870 1870 1871 1871 1875 1875 1880 1880 1881 1881 1885 1885 1890 1890 1891 1891 1900 1900 1901 1901 1910 1910 1911 1911 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 2014 2014 2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020 2020 YEAR gives the year in which the census or survey was taken. For samples that span years, the midpoint or first year of the interval is reported. IPUMS IPUMS sample identifier 032197001 Argentina 1970 032198001 Argentina 1980 032199101 Argentina 1991 032200101 Argentina 2001 032201001 Argentina 2010 051200101 Armenia 2001 051201101 Armenia 2011 040197101 Austria 1971 040198101 Austria 1981 040199101 Austria 1991 040200101 Austria 2001 040201101 Austria 2011 050199101 Bangladesh 1991 050200101 Bangladesh 2001 050201101 Bangladesh 2011 112199901 Belarus 1999 112200901 Belarus 2009 204197901 Benin 1979 204199201 Benin 1992 204200201 Benin 2002 204201301 Benin 2013 068197601 Bolivia 1976 068199201 Bolivia 1992 068200101 Bolivia 2001 068201201 Bolivia 2012 072198101 Botswana 1981 072199101 Botswana 1991 072200101 Botswana 2001 072201101 Botswana 2011 076196001 Brazil 1960 076197001 Brazil 1970 076198001 Brazil 1980 076199101 Brazil 1991 076200001 Brazil 2000 076201001 Brazil 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 116199801 Cambodia 1998 116200401 Cambodia 2004 116200801 Cambodia 2008 116201301 Cambodia 2013 116201901 Cambodia 2019 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124185201 Canada 1852 124187101 Canada 1871 124188101 Canada 1881 124189101 Canada 1891 124190101 Canada 1901 124191101 Canada 1911 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 124201101 Canada 2011 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 152201701 Chile 2017 156198201 China 1982 156199001 China 1990 156200001 China 2000 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 192201201 Cuba 2012 208178701 Denmark 1787 208180101 Denmark 1801 208184501 Denmark 1845 208188001 Denmark 1880 208188501 Denmark 1885 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 818184801 Egypt 1848 818186801 Egypt 1868 818198601 Egypt 1986 818199601 Egypt 1996 818200601 Egypt 2006 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 242201401 Fiji 2014 246201001 Finland 2010 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 276181901 Germany 1819 (Mecklenburg) 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 300201101 Greece 2011 320196401 Guatemala 1964 320197301 Guatemala 1973 320198101 Guatemala 1981 320199401 Guatemala 1994 320200201 Guatemala 2002 324198301 Guinea 1983 324199601 Guinea 1996 324201401 Guinea 2014 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 340196101 Honduras 1961 340197401 Honduras 1974 340198801 Honduras 1988 340200101 Honduras 2001 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 348201101 Hungary 2011 352170301 Iceland 1703 352172901 Iceland 1729 352180101 Iceland 1801 352190101 Iceland 1901 352191001 Iceland 1910 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 356200941 India 2009 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 364201101 Iran 2011 368199701 Iraq 1997 372190101 Ireland 1901 372191101 Ireland 1911 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 372201601 Ireland 2016 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 376200801 Israel 2008 380200101 Italy 2001 380201101 Italy 2011 380201121 Italy 2011 Q1 LFS 380201221 Italy 2012 Q1 LFS 380201321 Italy 2013 Q1 LFS 380201421 Italy 2014 Q1 LFS 380201521 Italy 2015 Q1 LFS 380201621 Italy 2016 Q1 LFS 380201721 Italy 2017 Q1 LFS 380201821 Italy 2018 Q1 LFS 380201921 Italy 2019 Q1 LFS 380202021 Italy 2020 Q1 LFS 384198801 Ivory Coast 1988 384199801 Ivory Coast 1998 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 418199501 Laos 1995 418200501 Laos 2005 418201501 Laos 2015 426199601 Lesotho 1996 426200601 Lesotho 2006 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 480199001 Mauritius 1990 480200001 Mauritius 2000 480201101 Mauritius 2011 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 484201501 Mexico 2015 484202001 Mexico 2020 484200521 Mexico 2005 Q1 LFS 484200522 Mexico 2005 Q2 LFS 484200523 Mexico 2005 Q3 LFS 484200524 Mexico 2005 Q4 LFS 484200621 Mexico 2006 Q1 LFS 484200622 Mexico 2006 Q2 LFS 484200623 Mexico 2006 Q3 LFS 484200624 Mexico 2006 Q4 LFS 484200721 Mexico 2007 Q1 LFS 484200722 Mexico 2007 Q2 LFS 484200723 Mexico 2007 Q3 LFS 484200724 Mexico 2007 Q4 LFS 484200821 Mexico 2008 Q1 LFS 484200822 Mexico 2008 Q2 LFS 484200823 Mexico 2008 Q3 LFS 484200824 Mexico 2008 Q4 LFS 484200921 Mexico 2009 Q1 LFS 484200922 Mexico 2009 Q2 LFS 484200923 Mexico 2009 Q3 LFS 484200924 Mexico 2009 Q4 LFS 484201021 Mexico 2010 Q1 LFS 484201022 Mexico 2010 Q2 LFS 484201023 Mexico 2010 Q3 LFS 484201024 Mexico 2010 Q4 LFS 484201121 Mexico 2011 Q1 LFS 484201122 Mexico 2011 Q2 LFS 484201123 Mexico 2011 Q3 LFS 484201124 Mexico 2011 Q4 LFS 484201221 Mexico 2012 Q1 LFS 484201222 Mexico 2012 Q2 LFS 484201223 Mexico 2012 Q3 LFS 484201224 Mexico 2012 Q4 LFS 484201321 Mexico 2013 Q1 LFS 484201322 Mexico 2013 Q2 LFS 484201323 Mexico 2013 Q3 LFS 484201324 Mexico 2013 Q4 LFS 484201421 Mexico 2014 Q1 LFS 484201422 Mexico 2014 Q2 LFS 484201423 Mexico 2014 Q3 LFS 484201424 Mexico 2014 Q4 LFS 484201521 Mexico 2015 Q1 LFS 484201522 Mexico 2015 Q2 LFS 484201523 Mexico 2015 Q3 LFS 484201524 Mexico 2015 Q4 LFS 484201621 Mexico 2016 Q1 LFS 484201622 Mexico 2016 Q2 LFS 484201623 Mexico 2016 Q3 LFS 484201624 Mexico 2016 Q4 LFS 484201721 Mexico 2017 Q1 LFS 484201722 Mexico 2017 Q2 LFS 484201723 Mexico 2017 Q3 LFS 484201724 Mexico 2017 Q4 LFS 484201821 Mexico 2018 Q1 LFS 484201822 Mexico 2018 Q2 LFS 484201823 Mexico 2018 Q3 LFS 484201824 Mexico 2018 Q4 LFS 484201921 Mexico 2019 Q1 LFS 484201922 Mexico 2019 Q2 LFS 484201923 Mexico 2019 Q3 LFS 484201924 Mexico 2019 Q4 LFS 484202021 Mexico 2020 Q1 LFS 484202023 Mexico 2020 Q3 LFS 496198901 Mongolia 1989 496200001 Mongolia 2000 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 504201401 Morocco 2014 508199701 Mozambique 1997 508200701 Mozambique 2007 104201401 Myanmar 2014 524200101 Nepal 2001 524201101 Nepal 2011 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 528201101 Netherlands 2011 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 578180101 Norway 1801 578186501 Norway 1865 578187501 Norway 1875 578190001 Norway 1900 578191001 Norway 1910 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 275199701 Palestine 1997 275200701 Palestine 2007 275201701 Palestine 2017 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 598198001 Papua New Guinea 1980 598199001 Papua New Guinea 1990 598200001 Papua New Guinea 2000 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 604201701 Peru 2017 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 608201001 Philippines 2010 616197801 Poland 1978 616198801 Poland 1988 616200201 Poland 2002 616201101 Poland 2011 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 630201501 Puerto Rico 2015 630202001 Puerto Rico 2020 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 642201101 Romania 2011 643200201 Russia 2002 643201001 Russia 2010 646199101 Rwanda 1991 646200201 Rwanda 2002 646201201 Rwanda 2012 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 686201301 Senegal 2013 694200401 Sierra Leone 2004 694201501 Sierra Leone 2015 703199101 Slovak Republic 1991 703200101 Slovak Republic 2001 703201101 Slovak Republic 2011 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 710201601 South Africa 2016 728200801 South Sudan 2008 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 724200521 Spain 2005 Q1 LFS 724200522 Spain 2005 Q2 LFS 724200523 Spain 2005 Q3 LFS 724200524 Spain 2005 Q4 LFS 724200621 Spain 2006 Q1 LFS 724200622 Spain 2006 Q2 LFS 724200623 Spain 2006 Q3 LFS 724200624 Spain 2006 Q4 LFS 724200721 Spain 2007 Q1 LFS 724200722 Spain 2007 Q2 LFS 724200723 Spain 2007 Q3 LFS 724200724 Spain 2007 Q4 LFS 724200821 Spain 2008 Q1 LFS 724200822 Spain 2008 Q2 LFS 724200823 Spain 2008 Q3 LFS 724200824 Spain 2008 Q4 LFS 724200921 Spain 2009 Q1 LFS 724200922 Spain 2009 Q2 LFS 724200923 Spain 2009 Q3 LFS 724200924 Spain 2009 Q4 LFS 724201021 Spain 2010 Q1 LFS 724201022 Spain 2010 Q2 LFS 724201023 Spain 2010 Q3 LFS 724201024 Spain 2010 Q4 LFS 724201121 Spain 2011 Q1 LFS 724201122 Spain 2011 Q2 LFS 724201123 Spain 2011 Q3 LFS 724201124 Spain 2011 Q4 LFS 724201221 Spain 2012 Q1 LFS 724201222 Spain 2012 Q2 LFS 724201223 Spain 2012 Q3 LFS 724201224 Spain 2012 Q4 LFS 724201321 Spain 2013 Q1 LFS 724201322 Spain 2013 Q2 LFS 724201323 Spain 2013 Q3 LFS 724201324 Spain 2013 Q4 LFS 724201421 Spain 2014 Q1 LFS 724201422 Spain 2014 Q2 LFS 724201423 Spain 2014 Q3 LFS 724201424 Spain 2014 Q4 LFS 724201521 Spain 2015 Q1 LFS 724201522 Spain 2015 Q2 LFS 724201523 Spain 2015 Q3 LFS 724201524 Spain 2015 Q4 LFS 724201621 Spain 2016 Q1 LFS 724201622 Spain 2016 Q2 LFS 724201623 Spain 2016 Q3 LFS 724201624 Spain 2016 Q4 LFS 724201721 Spain 2017 Q1 LFS 724201722 Spain 2017 Q2 LFS 724201723 Spain 2017 Q3 LFS 724201724 Spain 2017 Q4 LFS 724201821 Spain 2018 Q1 LFS 724201822 Spain 2018 Q2 LFS 724201823 Spain 2018 Q3 LFS 724201824 Spain 2018 Q4 LFS 724201921 Spain 2019 Q1 LFS 724201922 Spain 2019 Q2 LFS 724201923 Spain 2019 Q3 LFS 724201924 Spain 2019 Q4 LFS 724202021 Spain 2020 Q1 LFS 724202022 Spain 2020 Q2 LFS 724202023 Spain 2020 Q3 LFS 724202024 Spain 2020 Q4 LFS 729200801 Sudan 2008 740200401 Suriname 2004 740201201 Suriname 2012 752188001 Sweden 1880 752189001 Sweden 1890 752190001 Sweden 1900 752191001 Sweden 1910 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 756201101 Switzerland 2011 834198801 Tanzania 1988 834200201 Tanzania 2002 834201201 Tanzania 2012 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 768196001 Togo 1960 768197001 Togo 1970 768201001 Togo 2010 780197001 Trinidad and Tobago 1970 780198001 Trinidad and Tobago 1980 780199001 Trinidad and Tobago 1990 780200001 Trinidad and Tobago 2000 780201101 Trinidad and Tobago 2011 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 800201401 Uganda 2014 804200101 Ukraine 2001 826185101 United Kingdom 1851 (England and Wales) 826185102 United Kingdom 1851 (Scotland) 826185103 United Kingdom 1851 (2% sample) 826186101 United Kingdom 1861 (England and Wales) 826186102 United Kingdom 1861 (Scotland) 826187101 United Kingdom 1871 (Scotland) 826188101 United Kingdom 1881 (England and Wales) 826188102 United Kingdom 1881 (Scotland) 826189101 United Kingdom 1891 (England and Wales) 826189102 United Kingdom 1891 (Scotland) 826190101 United Kingdom 1901 (England and Wales) 826190102 United Kingdom 1901 (Scotland) 826191101 United Kingdom 1911 (England and Wales) 826196101 United Kingdom 1961 826197101 United Kingdom 1971 826199101 United Kingdom 1991 826200101 United Kingdom 2001 840185001 United States 1850 (100%) 840185002 United States 1850 (1%) 840186001 United States 1860 (1%) 840187001 United States 1870 (1%) 840188001 United States 1880 (100%) 840188002 United States 1880 (10%) 840190001 United States 1900 (5%) 840191001 United States 1910 (1%) 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 840201501 United States 2015 840202001 United States 2020 858196301 Uruguay 1963 858196302 Uruguay 1963 (full count) 858197501 Uruguay 1975 858197502 Uruguay 1975 (full count) 858198501 Uruguay 1985 858198502 Uruguay 1985 (full count) 858199601 Uruguay 1996 858199602 Uruguay 1996 (full count) 858200621 Uruguay 2006 858201101 Uruguay 2011 858201102 Uruguay 2011 (full count) 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 704201901 Vietnam 2019 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 716201201 Zimbabwe 2012 SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). IPUMS Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002Colombia 1993, 2005Costa Rica 1984, 2000Cuba 2002Dominican Republic 1981, 2002, 2010Ecuador 1990, 2001Germany 1971Hungary 1980, 1990, 2001Jamaica 1982, 1991, 2001Malaysia 1970, 1991, 2000Mexico 1995, 1990, 2000, 2005Nigeria 2006Panama 2000Peru 1993, 2007Portugal 1981, 1991, 2001Spain 1991Uruguay 2011Venezuela 1990, 2001Vietnam 1989In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. The U.S. 1900 sample and 1880 10% sample have multi-household dwellings that can be identified using the last 3 digits of SERIAL. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. IPUMS Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 4-digit numeric variable. IPUMS Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Subsample number 00 1st 1% subsample 01 2nd 1% subsample 02 3rd 1% subsample 03 4th 1% subsample 04 5th 1% subsample 05 6th 1% subsample 06 7th 1% subsample 07 8th 1% subsample 08 9th 1% subsample 09 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. IPUMS Group quarters (collective dwelling) status 00 Vacant 10 Households 20 Group quarters (collective), n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. IPUMS Number of unrelated persons 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ UNREL indicates the number of persons in the household who are unrelated to the head as defined in the variable RELATE. IPUMS Urban-rural status 1 Rural 2 Urban 9 Unknown URBAN indicates whether the household was located in a place designated as urban or as rural. IPUMS Continent and region of country 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia REGIONW identifies the continent and region of each country. IPUMS 1st subnational geographic level, world [consistent boundaries over time] GEOLEV1 indicates the major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. First administrative units in GEOLEV1 have been spatiotemporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV1 is a 6-digit numeric variable. GEOLEV1 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO1_BR. IPUMS 2nd subnational geographic level, world [consistent boundaries over time] GEOLEV2 indicates the second major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. Second administrative units in GEOLEV2 have been spatio-temporally harmonized to provide spatially consistent boundaries across samples in each country. GEOLEV2 is a 9-digit numeric variable. GEOLEV2 codes and labels can be found here. Codes, labels, frequencies, and information about boundary changes for each country can be found in the country specific harmonized variable e.g. GEO2_BR. IPUMS Population density of GEOLEV1 unit, in persons per square kilometer POPDENSGEO1 indicates the population density in persons per square kilometer of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO1 is an 8-digit string variable listing the population density in persons per square kilometer. IPUMS Population density of GEOLEV2 unit, in persons per square kilometer POPDENSGEO2 indicates the population density in persons per square kilometer of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. POPDENSGEO2 is a 12-digit string variable listing the population density in persons per square kilometer. IPUMS Area of GEOLEV1 unit in square kilometers AREAMOLLWGEO1 indicates the area in square kilometers of the major administrative unit in which the household was enumerated. The major administrative unit of the household is identified by the GEOLEV1 variable. The area of units in GEOLEV1 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO1 is a 10-digit string variable listing the area in square kilometers. IPUMS Area of GEOLEV2 unit in square kilometers AREAMOLLWGEO2 indicates the area in square kilometers of the second major administrative unit in which the household was enumerated. The second major administrative unit of the household is identified by the GEOLEV2 variable. The area of units in GEOLEV2 is calculated using Mollweide's equal area projection. For a full set of geography variables refer to IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. AREAMOLLWGEO2 is a 10-digit string variable listing the area in square kilometers. IPUMS Sudan, State 2008 [Level 1; consistent boundaries, GIS] 729011 Northern 729012 Nahr El Nil 729021 Red Sea 729022 Kassala 729023 Al Gedarif 729031 Khartoum 729041 Al Gezira 729042 White Nile 729043 Sinnar 729044 Blue Nile 729051 North Kordofan 729052 South Kordofan 729061 North Darfur 729062 West Darfur 729063 South Darfur GEO1_SD identifies the household's state within Sudan in 2008. States are the first level administrative units of the country. States are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_SD can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Sudan can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Sudan, State 2008 [Level 1, GIS] 011 Northern 012 Nahr El Nil 021 Red Sea 022 Kassala 023 Al Gedarif 031 Khartoum 041 Al Gezira 042 White Nile 043 Sinnar 044 Blue Nile 051 North Kordofan 052 South Kordofan 061 North Darfur 062 West Darfur 063 South Darfur GEO1_SD2008 identifies the household's state within Sudan in 2008. States are the first level administrative units of the country. A GIS map (in shapefile format), corresponding to GEO1_SD2008 can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Sudan can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Sudan, County 2008 [Level 2; consistent boundaries, GIS] 729011001 Halfa 729011002 Dalgo 729011003 Alborgaig 729011004 Dongola 729011005 Algolid 729011006 Aldaba 729011007 Marwai 729012001 Abu Hamed 729012002 Berber 729012003 Atbara 729012004 El Damar 729012005 Shendi 729012006 El Matama 729021001 Halayib 729021002 Elgunab 729021003 Port Sudan 729021004 Sawakin 729021005 Senkat 729021006 Haya 729021007 Toker 729021008 Agieg 729022001 North Aldalta 729022002 Hamashkoreeb 729022003 Talkook 729022004 Aroma rural 729022005 West Kassala 729022006 Kassala city 729022007 Kassala rural 729022008 Halfa Al Gedida 729022009 Nahr Atbara 729022010 Setit 729022011 Wad El Hilaiw 729023001 El Botana 729023002 El Fashaga 729023003 Central Al Gedarif 729023004 Al Gedarif city 729023005 Al Fau 729023006 El Rahad 729023007 Qala'a El Nahal 729023008 Al Galabat Al Garbia 729023009 El Ghoreisha 729023010 El Galabat Sharquia 729031001 Karrari 729031002 Om Bada 729031003 Om Durman 729031004 Bahri 729031005 Sharg Alneel 729031006 Khartoum 729031007 Jabel Awliya 729041001 El Gezira East 729041002 El Kamlin 729041003 El Hasaheisa 729041004 Um Algora 729041005 Wad Madni Alkobra 729041006 South Aljazeera 729041007 El Managil 729042001 El Geteina 729042002 Um Rimta 729042003 Eldiwiem 729042004 Rabak 729042005 El Jebelein 729042006 Kosti 729042007 Al Salam 729042008 Tandalti 729043001 East Sinnar 729043002 Sinnar 729043003 Eldindir 729043004 Alsoki 729043005 Sinja 729043006 Abu Hugar 729043007 Eldali 729044001 Elrosieris 729044002 Eldamazin 729044003 Al Tdamon 729044004 Bau 729044005 Giesan 729044006 Elkurmuk 729051001 Gabrat Elshiekh 729051002 Sodari 729051003 Bara 729051004 Um Rwaba 729051005 El Nohook 729051006 Shekan 729051007 Abu Zabad 729051008 Wad Banda 729051009 Gebieash 729052001 Alrashad 729052002 Abu Jibieha 729052003 El Dalanj 729052004 Kadogli 729052005 Al Salam 729052006 Talody 729052007 Lagawa 729052008 Kielak 729052009 Ab Yei 729061001 El Malha 729061002 Mellit 729061004 Sarf Omra 729061005 Alseraf 729061006 Kebkabiya 729061007 Kutum 729061008 Alkoma 729061009 El Fasher 729061010 Um Kedada 729061011 Kalmando 729061012 Altewash/Alleet 729061014 Alwaha 729062001 Kulbus 729062002 Sirba 729062003 Kirienik 729062004 El Geneina 729062005 Bayda 729062006 Habiela 729062007 Azoom 729062008 Zalingei, Nertiti 729062011 Wadi Salih 729062012 Mukjar 729062013 Um Dukhun 729063001 Sheiria 729063002 Nyala 729063004 Kass, East Jabal Mara 729063005 Ed Al Fursan 729063006 Al Salam 729063007 Ed Da'ein 729063008 Adiela 729063009 Tullus 729063010 Rihied El Birdi 729063011 Buram 729063012 Bahr Alarab GEO2_SD identifies the household's county within Sudan in 2008. Counties are the second level administrative units of the country, after states. A GIS map (in shapefile format), corresponding to GEO2_SD can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Sudan can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Sudan, County 2008 [Level 2, GIS] 011001 Halfa 011002 Dalgo 011003 Alborgaig 011004 Dongola 011005 Algolid 011006 Aldaba 011007 Marwai 012001 Abu Hamed 012002 Berber 012003 Atbara 012004 El Damar 012005 Shendi 012006 El Matama 021001 Halayib 021002 Elgunab 021003 Port Sudan 021004 Sawakin 021005 Senkat 021006 Haya 021007 Toker 021008 Agieg 022001 North Aldalta 022002 Hamashkoreeb 022003 Talkook 022004 Aroma rural 022005 West Kassala 022006 Kassala city 022007 Kassala rural 022008 Halfa Al Gedida 022009 Nahr Atbara 022010 Setit 022011 Wad El Hilaiw 023001 El Botana 023002 El Fashaga 023003 Central Al Gedarif 023004 Al Gedarif city 023005 Al Fau 023006 El Rahad 023007 Qala'a El Nahal 023008 Al Galabat Al Garbia 023009 El Ghoreisha 023010 El Galabat Sharquia 031001 Karrari 031002 Om Bada 031003 Om Durman 031004 Bahri 031005 Sharg Alneel 031006 Khartoum 031007 Jabel Awliya 041001 El Gezira East 041002 El Kamlin 041003 El Hasaheisa 041004 Um Algora 041005 Wad Madni Alkobra 041006 South Aljazeera 041007 El Managil 042001 El Geteina 042002 Um Rimta 042003 Eldiwiem 042004 Rabak 042005 El Jebelein 042006 Kosti 042007 Al Salam 042008 Tandalti 043001 East Sinnar 043002 Sinnar 043003 Eldindir 043004 Alsoki 043005 Sinja 043006 Abu Hugar 043007 Eldali 044001 Elrosieris 044002 Eldamazin 044003 Al Tdamon 044004 Bau 044005 Giesan 044006 Elkurmuk 051001 Gabrat Elshiekh 051002 Sodari 051003 Bara 051004 Um Rwaba 051005 El Nohook 051006 Shekan 051007 Abu Zabad 051008 Wad Banda 051009 Gebieash 052001 Alrashad 052002 Abu Jibieha 052003 El Dalanj 052004 Kadogli 052005 Al Salam 052006 Talody 052007 Lagawa 052008 Kielak 052009 Ab Yei 061001 El Malha 061002 Mellit 061004 Sarf Omra 061005 Alseraf 061006 Kebkabiya 061007 Kutum 061008 Alkoma 061009 El Fasher 061010 Um Kedada 061011 Kalmando 061012 Altewash/Alleet 061014 Alwaha 062001 Kulbus 062002 Sirba 062003 Kirienik 062004 El Geneina 062005 Bayda 062006 Habiela 062007 Azoom 062008 Zalingei, Nertiti 062011 Wadi Salih 062012 Mukjar 062013 Um Dukhun 063001 Sheiria 063002 Nyala 063004 Kass, East Jabal Mara 063005 Ed Al Fursan 063006 Al Salam 063007 Ed Da'ein 063008 Adiela 063009 Tullus 063010 Rihied El Birdi 063011 Buram 063012 Bahr Alarab GEO2_SD2008 indicates the household’s county within Sudan in 2008. Counties are the second level administrative units of the country, after states. A GIS map (in shapefile format), corresponding to GEO2_SD2008 can be downloaded from the GIS Boundary files page in the IPUMS International web site The full set of geography variables for Sudan can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level of any country refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS Sudan, Region 1 Northern 2 Eastern 3 Khartoum 4 Central 5 Kordofan 6 Darfur REGNSD indicates the regions in Sudan in which the household was enumerated. Regions are the largest-scale geographic identifier of the country. REGNSD is harmonized solely based on the names of the geographical unit. It does not take into account the changes that may have occurred in the political boundaries of the units. The full set of geography variables for Sudan can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1 and GEOLEV2. More information on IPUMS-International geography can be found here. IPUMS DHS-IPUMS-I Sudan regions, 1989-2008 [consistent boundaries, GIS] 1 Khartoum 2 Northern 3 Eastern 4 Central 5 Kordofan 6 Darfur DHS_IPUMSI_SD provides geographic codes for Sudan that match those in the DHS and IPUMS-International databases. This variable can be used to link contextual area data from IPUMS-DHS to IPUMS-International or vice versa. The codes in DHS_IPUMSI_SD indicate the major administrative unit in which the household was enumerated or surveyed. GIS shapefiles for Sudan can be downloaded here. IPUMS Ownership of dwelling [general version] NIU (not in universe) 1 Owned 2 Not owned 9 Unknown OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. IPUMS Ownership of dwelling [detailed version] 000 NIU (not in universe) 100 Owned 110 Owned, already paid 120 Owned, still paying 130 Owned, constructed 140 Owned, inherited 190 Owned, other 191 Owned, house 192 Owned, condominium 193 Apartment proprietor 194 Shared ownership 200 Not owned 210 Renting, not specified 211 Renting, government 212 Renting, local authority 213 Renting, parastatal 214 Renting, private 215 Renting, private company 216 Renting, individual 217 Renting, collective 218 Renting, joint state and individual 219 Renting, public subsidized 220 Renting, private subsidized 221 Renting, co-tenant 222 Renting, relative of tenant 223 Renting, cooperative 224 Renting, with a job or business 225 Renting, loan-backed habitation 226 Renting, mixed contract 227 Furnished dwelling 228 Sharecropping 230 Subletting 231 Rent to own 239 Renting, other 240 Occupied de facto/squatting 250 Free/usufruct (no cash rent) 251 Free, provided by employer 252 Free, without work or services 253 Free, provided by family or friend 254 Free, private 255 Free, public 256 Free, condemned 257 Free, other 260 Endowment, Waqf (Egypt historical) 290 Not owned, other 999 Unknown OWNERSHIP indicates whether a member of the household owned the housing unit. Households that acquired their unit with a mortgage or other lending arrangement were understood to "own" their unit even if they had not yet completed repayment. For those that did not own their housing unit, several options were possible: renting (from various types of owners), subletting, usufruct, and de facto occupation. IPUMS Main source of livelihood 00 NIU (not in universe) 10 Agricultural activities 11 Subsistence animal husbandry 12 Subsistence farming 13 Commercial farming 14 Fishing 20 Employment income 30 Business enterprise 31 Formal trading 32 Petty trading 40 Cottage industry 50 Property income 60 Family support/remittances 70 Humanitarian aid 80 Other 81 Rent or remittances 82 Religious work 83 Pension 84 Sale of assets 99 Unknown LIVEHOOD describes the main source of livelihood of the household. If there were multiple sources, one had to be chosen as the most important. IPUMS Electricity NIU (not in universe) 1 Yes 2 No 9 Unknown ELECTRIC indicates whether the household had access to electricity. IPUMS Water supply 00 NIU (not in universe) 10 Yes, piped water 11 Piped inside dwelling 12 Piped, exclusively to this household 13 Piped, shared with other households 14 Piped outside the dwelling 15 Piped outside dwelling, in building 16 Piped within the building or plot of land 17 Piped outside the building or lot 18 Have access to public piped water 20 No piped water 99 Unknown WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water. IPUMS Cooking fuel 00 NIU (not in universe) 10 None 20 Electricity 30 Petroleum gas, unspecified 31 Gas -- piped/utility 32 Gas -- tanked or bottled 33 Propane 34 Liquefied petroleum gas 35 Gas -- piped and bottled 40 Petroleum liquid 41 Oil, kerosene, and other liquid fuels 42 Kerosene/paraffin 43 Kerosene or oil 44 Kerosene or gasoline 45 Gasoline 46 Cocinol 47 Diesel 50 Wood, coal, and other solid fuels 51 Wood and other plant fuels 52 Non-wood plant materials 53 Coal or charcoal 54 Charcoal 55 Coal 56 Wood or charcoal 60 Multiple fuels 61 Bottled gas and wood 62 Propane and electricity 63 Propane, kerosene, and electricity 64 Propane and kerosene 65 Kerosene and electrictiy 66 Other combinations 70 Other 71 Alcohol 72 Biogas 73 Discarded or waste material 74 Dung/manure 75 Other combined organic waste materials 76 Solar energy 77 Candle 99 Unknown/missing FUELCOOK indicates the predominant type of fuel or energy used for cooking. IPUMS Telephone availability NIU (not in universe) 1 No 2 Yes 9 Unknown/missing PHONE indicates the availability of a telephone in the dwelling. IPUMS Cellular phone availability NIU (not in universe) 1 Yes 2 No 9 Unknown CELL indicates the availability of a cellular phone in the household. IPUMS Automobiles available No autos 1 1 auto 2 2 autos 3 3 autos 4 4 autos 5 5 autos 6 6+ autos 7 Have auto, number unspecified 8 Unknown 9 NIU (not in universe) AUTOS records whether a member of the household owned or had use of a vehicle and, in many samples, the number of such vehicles. IPUMS Air conditioning 00 NIU (not in universe) 10 No air conditioning 20 Yes, air conditioning 21 1 unit or room 22 2 units or rooms 23 3 units or rooms 24 4 units or rooms 25 5 units or rooms 26 6 units or rooms 27 7 units or rooms 28 8 or more units or rooms 29 Central system 99 Unknown This variable indicates whether the household had air conditioning. IPUMS Computer NIU (not in universe) 1 No 2 Yes 9 Unknown/missing COMPUTER indicates whether the household had a personal computer. IPUMS Refrigerator NIU (not in universe) 1 No 2 Yes 9 Unknown/missing REFRIG indicates whether the household had a refrigerator. IPUMS Television set 00 NIU (not in universe) 10 No 20 Yes, color or black-and-white not specified 21 1 television 22 2 televisions 23 3 televisions 24 4 televisions 25 5 televisions 26 6 televisions 27 7 televisions 28 8 televisions 29 9+ televisions 30 Yes, at least one color tv 31 1 color tv 32 2 color tvs 33 3+ televisions 40 Yes, black-and-white only 41 1 black-white tv 42 2 black-white tvs 43 3+ black-white tvs 99 Unknown/missing TV indicates whether the household had a television. IPUMS Radio in household NIU (not in universe) 1 No 2 Yes 9 Unknown/missing RADIO indicates whether the household had a radio. IPUMS Number of bedrooms 00 No bedrooms 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) BEDROOMS indicates the number of rooms available to members of the household for sleeping. IPUMS Toilet 00 NIU (not in universe) 10 No toilet 11 No flush toilet 20 Have toilet, type not specified 21 Flush toilet 22 Non-flush, latrine 23 Non-flush, other and unspecified 99 Unknown TOILET indicates whether the household had access to a toilet and, in most cases, whether it was a flush toilet or other type of installation. IPUMS Number of deaths in household last year None 1 1 death 2 2 deaths 3 3 deaths 4 4 deaths 5 5 deaths 6 6 deaths 7 7 or more deaths 8 Unknown 9 NIU (not in universe) MORTNUM indicates the number of deaths in the household in the past year. IPUMS Any deaths in household last year 1 Yes 2 No 8 Unknown/missing 9 NIU (not in universe) ANYMORT indicates whether there were any deaths in the household in the past year. IPUMS Household classification 00 Vacant household 01 One-person household 02 Married/cohab couple, no children 03 Married/cohab couple with children 04 Single-parent family 05 Polygamous family 06 Extended family, relatives only 07 Composite household, family and non-relatives 08 Non-family household 09 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. IPUMS Number of families in household Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families NFAMS is a constructed variable that indicates the number of families within each household. Family membership is defined by FAMUNIT. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and a domestic employee contains two families; a household consisting of a large, multi-generation extended family with no persons unrelated to the head counts as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. IPUMS Number of married couples in household No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). IPUMS Number of mothers in household No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). IPUMS Number of fathers in household No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). IPUMS Head's location in household HEADLOC gives the person number (PERNUM) of the head of household in samples in which persons are organized into households. HEADLOC is a 3-digit numeric variable. IPUMS Dwelling number Sudan 2008: All households This variable indicates the dwelling number. This is a 7-digit numeric variable with 0 implied decimal places IPUMS Number of persons in household Sudan 2008: All households 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 This variable indicates the number of persons in the household. IPUMS Dwelling created by splitting apart a large dwelling or household Sudan 2008: All households No problem 1 Yes: households within a large dwelling were split apart into separate dwellings 2 Yes: persons within a large household were split apart into separate dwellings This variable indicates whether the dwelling was created by splitting apart a large dwelling or household. IPUMS Region <svar a="all" v="SD08A022 SD08A023 SD08A024 SD08A025 SD08A026 SD08A027 SD08A028 SD08A031">State _ _<br />County / Mahaliya _ _<br />Payam / Administrative unit _ _<br />Boma / Popular Administrative unit _ _ _<br />Enumeration Area number _ _ _<br />Town / village / nomad camp _ _<br />Household number _ _ _<br /></svar> Sudan 2008: All households 1 Northern 2 Eastern 3 Khartoum 4 Central 5 Kordofan 6 Darfur This variable indicates the region the dwelling is located. IPUMS Urban/rural/nomad Sudan 2008: All households 1 Urban 2 Rural 3 Nomad This variable indicates whether the dwelling is in an urban or rural area, or the household is nomadic. IPUMS Type of household <svar a="all" v="SD08A032 SD08A137">Population group/type of household<br /><div class="i1">[] 1 Private household<br />[] 2 Nomads<br />[] 3 Internally displaced<br />[] 4 Institutional household<br />[] 5 Homeless<br />[] 6 Refugees<br />[] 7 Cattle camp<br />[] 8 Overnight travelers</div><br /></svar> Sudan 2008: All households 1 Private household 2 Nomads 3 Internally displaced 6 Refugees This variable indicates the type of household. IPUMS Type of dwelling <svar a="all" v="SD08A036 SD08A138">33. What type of dwelling does this household live in?<br /><div class="i1">[] 1 Tent<br />[] 2 Dwelling of straw mats<br />[] 3 Tukul / gottiya -- mud<br />[] 4 Tukul / gottiya -- sticks<br />[] 5 Flat or apartment<br />[] 6 Villa<br />[] 7 House of one floor -- mud<br />[] 8 House of one floor -- brick/concrete<br />[] 9 House constructed of wood<br />[] 10 Multi-storey house<br />[] 11 Incomplete</div><br /></svar> Sudan 2008: All households 01 Tent 02 Dwelling of straw mats 03 Tukul /gottiya of mud 04 Tukul /gottiya of sticks 05 Flat or apartment 06 Villa 07 House of one floor, mud 08 House of one floor, brick/concrete 09 House constructed of wood 10 Multi-story house 11 Incomplete This variable indicates the physical type of dwelling used by the household. IPUMS Number of sleeping rooms <svar a="all" v="SD08A037 SD08A139">34. How many rooms does this household use for sleeping indoors?<br /><div class="i1">_ _</div><br /></svar> Sudan 2008: All households 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ This variable indicates the number of rooms used by the household for sleeping. IPUMS Tenure status <svar a="all" v="SD08A038 SD08A140">35. What is the tenure status of this dwelling?<br /><div class="i1">[] 1 Owned<br />[] 2 Rented<br />[] 3 Housing provided as part of work<br />[] 4 Free</div><br /></svar> Sudan 2008: All households 1 Owned 2 Rented 3 Housing provided by job 4 Free This variable indicates the tenure status of the dwelling. IPUMS Source of drinking water <svar a="all" v="SD08A039 SD08A141">36. What is the main source of drinking water for this household?<br /><div class="i1">[] 1 Water filtering stations with common network/stand pipe (koshk)<br />[] 2 Mechanical boreholes with common network stand pipe (koshk)<br />[] 3 Deep boreholes (donkey) with network<br />[] 4 Deep boreholes (donkey) without network<br />[] 5 Hand pumps<br />[] 6 Sand filters with common network stand pipe (koshk)<br />[] 7 Shallow wells (dug wells)<br />[] 8 Hafeer / dam without filter (still open water)<br />[] 9 Hafeer /dam with filter (still open water)<br />[] 10 Turda / fula / river (still open water)<br />[] 11 Running open water source (river, pond, tura'a)<br />[] 12 Water vendor (tanker-cart-bearer) from deep boreholes<br />[] 13 Water vendor - from shallow wells pond/river/spring</div><br /></svar> Sudan 2008: All households 01 Water filtering station with common network 02 Mechanical boreholes with common network 03 Deep borehole (donkey) with network 04 Deep borehole (donkey) without network 05 Hand pump 06 Sand filter with common network 07 Shallow well (dug well) 08 Hafeer/Dam without filter (still open water) 09 Hafeer/Dam with filter (still open water) 10 Seasonal river (fula) 11 River, stream (turaa) 12 Water vendor (from deep borehole) 13 Water vendor (from shallow well, pond, river, spring) This variable indicates the main source of drinking water for the household. IPUMS Source of lighting <svar a="all" v="SD08A040 SD08A142">37. What is the main source of lighting for this household?<br /><div class="i1">[] 1 No lighting<br />[] 2 Public electricity<br />[] 3 Private electricity (generator)<br />[] 4 Gas<br />[] 5 Paraffin lantern<br />[] 6 Paraffin lamp<br />[] 7 Firewood<br />[] 8 Grass<br />[] 9 Candle wax<br />[] 10 Solar power<br />[] 11 Biogas</div><br /></svar> Sudan 2008: All households 01 No lighting 02 Public electricity 03 Private electricity (generator) 04 Gas 05 Paraffin lantern 06 Paraffin lamp 07 Firewood 08 Grass 09 Candle wax 10 Solar power 11 Biogas This variable indicates the main source of lighting for the household. IPUMS Cooking fuel <svar a="all" v="SD08A041 SD08A143">38. What is the main source of energy used for cooking in this household?<br /><div class="i1">[] 1 Firewood<br />[] 2 Charcoal<br />[] 3 Gas<br />[] 4 Electricity<br />[] 5 Paraffin<br />[] 6 Cow dung<br />[] 7 Grass<br />[] 8 Biogas<br />[] 9 No cooking</div><br /></svar> Sudan 2008: All households 1 Firewood 2 Charcoal 3 Gas 4 Electricity 5 Paraffin 6 Cow dung 7 Grass 8 Biogas 9 No cooking This variable indicates the main type of cooking fuel used in the household. IPUMS Toilet facilities <svar a="all" v="SD08A042 SD08A144">39. What is the main type of toilet facility used by this household?<br /><div class="i1">[] 1 Pit latrine private<br />[] 2 Shared pit latrine<br />[] 3 Private flush toilet<br />[] 4 Shared flush toilet<br />[] 5 Bucket toilet<br />[] 6 No toilet facility</div><br /></svar> Sudan 2008: All households 1 Pit latrine private 2 Pit latrine shared 3 Flush toilet private 4 Flush toilet shared 5 Bucket toilet 6 No toilet facility This variable indicates the main type of toilet facility used by the household. IPUMS Motor vehicle <svar a="all" v="SD08A043 SD08A044 SD08A045 SD08A046 SD08A047 SD08A048 SD08A049 SD08A145 SD08A146 SD08A147 SD08A148 SD08A149 SD08A150 SD08A151">40. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Motor vehicle<br />[] 2 Motor cycle / motor rickshaw<br />[] 3 Bicycle<br />[] 4 Canoe / boat<br />[] 5 Any type of animal used for transport<br />[] 6 Tractor<br />[] 7 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a motor vehicle. IPUMS Motorcycle <svar a="all" v="SD08A043 SD08A044 SD08A045 SD08A046 SD08A047 SD08A048 SD08A049 SD08A145 SD08A146 SD08A147 SD08A148 SD08A149 SD08A150 SD08A151">40. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Motor vehicle<br />[] 2 Motor cycle / motor rickshaw<br />[] 3 Bicycle<br />[] 4 Canoe / boat<br />[] 5 Any type of animal used for transport<br />[] 6 Tractor<br />[] 7 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a motorcycle. IPUMS Bicycle <svar a="all" v="SD08A043 SD08A044 SD08A045 SD08A046 SD08A047 SD08A048 SD08A049 SD08A145 SD08A146 SD08A147 SD08A148 SD08A149 SD08A150 SD08A151">40. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Motor vehicle<br />[] 2 Motor cycle / motor rickshaw<br />[] 3 Bicycle<br />[] 4 Canoe / boat<br />[] 5 Any type of animal used for transport<br />[] 6 Tractor<br />[] 7 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a bicycle. IPUMS Canoe/boat <svar a="all" v="SD08A043 SD08A044 SD08A045 SD08A046 SD08A047 SD08A048 SD08A049 SD08A145 SD08A146 SD08A147 SD08A148 SD08A149 SD08A150 SD08A151">40. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Motor vehicle<br />[] 2 Motor cycle / motor rickshaw<br />[] 3 Bicycle<br />[] 4 Canoe / boat<br />[] 5 Any type of animal used for transport<br />[] 6 Tractor<br />[] 7 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a canoe/boat. IPUMS Animal transport <svar a="all" v="SD08A043 SD08A044 SD08A045 SD08A046 SD08A047 SD08A048 SD08A049 SD08A145 SD08A146 SD08A147 SD08A148 SD08A149 SD08A150 SD08A151">40. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Motor vehicle<br />[] 2 Motor cycle / motor rickshaw<br />[] 3 Bicycle<br />[] 4 Canoe / boat<br />[] 5 Any type of animal used for transport<br />[] 6 Tractor<br />[] 7 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns an animal that is used for transport. IPUMS Tractor <svar a="all" v="SD08A043 SD08A044 SD08A045 SD08A046 SD08A047 SD08A048 SD08A049 SD08A145 SD08A146 SD08A147 SD08A148 SD08A149 SD08A150 SD08A151">40. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Motor vehicle<br />[] 2 Motor cycle / motor rickshaw<br />[] 3 Bicycle<br />[] 4 Canoe / boat<br />[] 5 Any type of animal used for transport<br />[] 6 Tractor<br />[] 7 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a tractor. IPUMS No transport <svar a="all" v="SD08A043 SD08A044 SD08A045 SD08A046 SD08A047 SD08A048 SD08A049 SD08A145 SD08A146 SD08A147 SD08A148 SD08A149 SD08A150 SD08A151">40. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Motor vehicle<br />[] 2 Motor cycle / motor rickshaw<br />[] 3 Bicycle<br />[] 4 Canoe / boat<br />[] 5 Any type of animal used for transport<br />[] 6 Tractor<br />[] 7 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates if none of the household members own a form of transport, including animals. IPUMS Television <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a television. IPUMS Radio <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a radio. IPUMS Mobile phone <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a mobile phone. IPUMS Fixed phone <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a fixed phone. IPUMS Computer <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a computer. IPUMS Refrigerator <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a refrigerator. IPUMS Satellite dish <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a satellite dish. IPUMS Fan <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns a fan. IPUMS Air cooler/AC <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether any member of the household owns an air cooler or A/C unit. IPUMS No household amenities <svar a="all" v="SD08A050 SD08A051 SD08A052 SD08A053 SD08A054 SD08A055 SD08A056 SD08A057 SD08A058 SD08A059 SD08A152 SD08A153 SD08A154 SD08A155 SD08A156 SD08A157 SD08A158 SD08A159 SD08A160 SD08A161">41. Does any member of this household own any of the following? <br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Television<br />[] 2 Radio/transistor<br />[] 3 Mobile phone<br />[] 4 Fixed phone (landline)<br />[] 5 Computer<br />[] 6 Refrigerator<br />[] 7 Satellite dish<br />[] 8 Fan<br />[] 9 Air cooler / air-conditioner<br />[] 10 None</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates if none of the household members own any of the mentioned household amenities. IPUMS Source of livelihood <svar a="all" v="SD08A060 SD08A162">42. What is the household's main source of livelihood?<br /><div class="i1">[] 1 Subsistence crop farming<br />[] 2 Subsistence animal husbandry<br />[] 3 Wages and salaries<br />[] 4 Owned business enterprise<br />[] 5 Property income<br />[] 6 Remittance<br />[] 7 Pension<br />[] 8 Humanitarian aid</div><br /></svar> Sudan 2008: All households 1 Subsistence crop farming 2 Subsistence animal husbandry 3 Wages and salaries 4 Owned business enterprise 5 Property income 6 Remittances 7 Pension 8 Humanitarian aid This variable indicates the household's main source of livelihood. IPUMS Any cultivation/plantation <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A061 SD08A163">43. Does this household perform any cultivation/plantation activities?<br /><div class="i1">[] 1 Yes<br />[] 2 No (skip to Q47)</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether the household performs any cultivation/plantation activities. IPUMS Area of cultivation/plantation <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A062 SD08A164">44. How large is the area being cultivated by this household? Code area in Feddans. If more than 999, mark "999".<br /><div class="i1">[Q44 was asked of households that are engaged in cultivation or plantation activities, as per Q43.]<br /><br />Area _ _ _</div><br /></svar> Sudan 2008: All households 000 No cultivation/plantation 001 1 feddan 002 2 feddans 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 to 34 035 35 to 39 040 40 to 44 045 45 to 49 050 50 to 54 055 55 to 59 060 60 to 64 065 65 to 69 070 70 to 74 075 75 to 79 080 80 to 84 085 85 to 89 090 90 to 94 095 95 to 99 100 100 to 109 110 110 to 119 120 120 to 129 130 130 to 139 140 140 to 149 150 150 to 159 160 160 to 169 170 170 to 179 180 180 to 189 190 190 to 199 200 200 to 219 220 220 to 239 240 240 to 259 260 260 to 279 280 280 to 299 300 300 to 319 320 320 to 339 340 340 to 359 360 360 to 379 380 380 to 399 400 400 to 419 420 420 to 439 440 440 to 459 460 460 to 479 480 480 to 499 500 500 to 519 520 520 to 539 540 540 to 559 560 560 to 579 580 580 to 599 600 600 to 619 620 620 to 639 640 640 to 659 660 660 to 679 680 680 to 699 700 700 to 719 720 720 to 739 740 740 to 759 760 760 to 779 780 780 to 799 800 800 to 819 820 820 to 839 840 840 to 859 860 860 to 879 880 880 to 899 900 900 to 919 920 920 to 939 940 940 to 959 960 960 to 979 980 980 to 998 999 999 or more feddans This variable indicates the area, in feddans, used for cultivation/plantation by this household. Above 29 feddans, the areas are grouped into intervals. IPUMS Cereals <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated cereals during the previous year. IPUMS Vegetables and melons <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated vegetables and melons during the previous year. IPUMS Fruits and nuts <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated fruits and nuts during the previous year. IPUMS Oilseed crops <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated oilseed crops during the previous year. IPUMS Root and tuber crops <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated root and tuber crops during the previous year. IPUMS Beverage and spice crops <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated beverage and spice crops during the previous year. IPUMS Leguminous crops <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the household cultivated leguminous crops during the previous year. IPUMS Sugar crops <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the household cultivated sugar crops during the previous year. IPUMS Cotton <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the household cultivated cotton during the previous year. IPUMS Coffee <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated coffee during the previous year. IPUMS Tea <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated tea during the previous year. IPUMS Other crop <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar v=" SD08A063 SD08A064 SD08A065 SD08A066 SD08A067 SD08A068 SD08A069 SD08A071 SD08A072 SD08A073 SD08A074 SD08A165 SD08A166 SD08A167 SD08A168 SD08A169 SD08A170 SD08A171 SD08A172 SD08A173 SD08A174 SD08A175 SD08A176">45. What type of crops did this household cultivate during the previous year? <br /><div class="i1">[Q45 was asked of households that are engaged in cultivation or plantation activities, per Q43]<br /><br />(Mark all that apply)<br /><br />[] 1 Cereals<br />[] 2 Vegetables<br />[] 3 Fruits and nuts<br />[] 4 Oil seed<br />[] 5 Root and tuber<br />[] 6 Beverage/spice<br />[] 7 Leguminous<br />[] 8 Sugar<br />[] 9 Cotton<br />[] 10 Coffee<br />[] 11 Tea<br />[] 12 Other</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether this household cultivated other crops besides those mentioned above during the previous year. IPUMS Tenure status of land <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A075 SD08A177"> 46. What is the tenure status of land under cultivation/plantation?<br /><div class="i1">[Q46 was asked of households that are engaged in cultivation or plantation activities, as per Q43.]<br /><br />[] 1 Owned<br />[] 2 Rented<br />[] 3 Partially owned<br />[] 4 Communal</div><br /></svar> Sudan 2008: Households that cultivate land [discrepancies: none] 1 Owned 2 Rented 3 Partially owned 4 Communal 9 NIU (not in universe) This variable indicates the tenure status of the land under cultivation/plantation. IPUMS Fishery <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A076 SD08A178">47. Does this household perform any fishery activities?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> Sudan 2008: All households 1 Yes 2 No This variable indicates whether the household performs any fishery activities. IPUMS Cattle <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of cattle the household owns. SD08A077 is a 3-digit numeric variable. Top codes:999 = 999+ IPUMS Camels <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of camels the household owns. SD08A078 is a 1-digit numeric variable. Top codes:9 = 9+ IPUMS Sheep <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of sheep the household owns. SD08A079 is a 3-digit numeric variable. Top codes:999 = 999+ IPUMS Goats <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of goats the household owns. SD08A080 is a 3-digit numeric variable. Top codes:999 = 999+ IPUMS Horses <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of horses the household owns. SD08A081 is a 1-digit numeric variable. Top codes:3 = 3+ IPUMS Donkeys <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of donkeys the household owns. SD08A082 is a 2-digit numeric variable. From 20 donkeys onwards, the variable is coded in intervals. Top codes:40 = 40+ IPUMS Pigs <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of pigs the household owns. SD08A083 is a 2-digit numeric variable. Top codes:20 = 20+ IPUMS Poultry <span class="em">For households engaged in cultivation/plantation, animal husbandry, fishery</span> <br />[Questions 43 - 48]</p> <p><svar a="all" v="SD08A077 SD08A078 SD08A079 SD08A080 SD08A081 SD08A082 SD08A083 SD08A084 SD08A179 SD08A180 SD08A181 SD08A182 SD08A183 SD08A184 SD08A185 SD08A186">48. Does this household own any of the following animals? Code the number for all that apply, if more than 999, code "999")<br /><div class="i1">Cattle _ _ _<br />Camels _ _ _<br />Sheep _ _ _<br />Goats _ _ _<br />Horses _ _ _<br />Donkeys _ _ _<br />Pigs _ _ _<br />Poultry _ _ _</div><br /></svar> Sudan 2008: All households This variable indicates the number of poultry the household owns. SD08A084 is a 3-digit numeric variable. Top codes:100 = 100+ IPUMS Deaths in last 12 months <svar a="all" v="SD08A085 SD08A187">49. Was there any deaths among members of the household in the past 12 months?<br /><div class="i1">[] 1 Yes (list names)<br />[] 2 No (end interview)</div><br /></svar> Sudan 2008: All households 1 Yes 2 No 9 Unknown This variable indicates whether there were any deaths among household members in the last 12 months. IPUMS Flag: type of household Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: type of dwelling Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: number of rooms Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: tenure Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: source of drinking water Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: source of lighting Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: cooking fuel Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: toilet facilities Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: motor vehicle Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: motorcycle Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: bicycle Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: canoe/boat Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: animal transport Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: tractor Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: no transport Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: television Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: radio Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: mobile phone Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: fixed phone Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: computer Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: refrigerator Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: satellite dish Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: fan Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: air cooler/ac Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: no household amenities Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: source of livelihood Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: any cultivation/plantation Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: area of cultivation/plantation Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: cereals Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: vegetables Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: fruits and nuts Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: oil seed Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: root and tuber crops Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: beverage/spice Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: leguminous crops Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: sugar Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: cotton Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: coffee Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: tea Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: other crop Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: tenure status of land Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: fishery Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: cattle Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: camels Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: sheep Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: goats Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: horses Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: donkeys Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: pigs Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: poultry Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: deaths in last 12 months Sudan 2008: All households No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Housing weight Sudan 2008: All households This variable indicates the housing weight. This is a 6-digit numeric variable with 4 implied decimal places IPUMS Number of death records Sudan 2008: All households 1 1 2 2 3 3 4 4 5 5 6 6 7 7+ This variable indicates the number of death records. IPUMS Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 4-digit numeric variable. IPUMS Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of MOMLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. To restrict MOMLOC to biological mothers, such as for own children fertility estimation, MOMLOC should be reset to zero when STEPMOM is greater than zero. MOMLOC is a 3-digit numeric variable. Codes0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother IPUMS Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. For more details on the construction of POPLOC, see the Comparability section of PARRULE and this paper on IPUMSI family linking methodology. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. To restrict POPLOC to biological mothers, such as for own children fertility estimation, POPLOC should be reset to zero when STEPPOP is greater than zero. POPLOC is a 3-digit numeric variable. Codes0 = No father of this person present in the household. 1 or higher = The person number of this person's father IPUMS Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. For more details on the construction of SPLOC, see the Comparability section of SPRULE and this paper on IPUMSI family linking methodology. SPLOC is a 3-digit numeric variable. Codes0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse IPUMS Rule for linking parent 00 No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap PARRULE describes the criteria by which the IPUMS International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Rule for linking spouse 00 No spouse present 01 Rule 1: strong relationship pairing, couple adjacent 02 Rule 2: strong relationship pairing, couple not adjacent 03 Rule 3: weak relationship pairing, couple adjacent 04 Rule 4: weak relationship pairing, couple not adjacent 05 Rule 5: weak consensual union pairings 06 Rule 6: sample-specific rules (usually child-to-child) SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Probable stepmother Biological mother or no mother present 1 Mother has no children born or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children born or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. In cases where more than one criterion for a likely stepmother is met, STEPMOM will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. IPUMS Probable stepfather Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible 4 Spouse of mother 5 Identified as adopted 6 Surname difference -- male child or never-married female STEPPOP indicates whether a person's father, as identified by POPLOC, was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. In cases where more than one criterion for a likely stepfather is met, STEPPOP will take the value of the criterion with the lowest code. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. IPUMS Man with more than one wife linked No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Woman is second or higher order wife Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 4-digit numeric variable. CodesIf there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. IPUMS Number of own family members in household 0001 1 family member present 0002 2 family members present 0003 3 family members present 0004 4 0005 5 0006 6 0007 7 0008 8 0009 9 0010 10 0011 11 0012 12 0013 13 0014 14 0015 15 0016 16 0017 17 0018 18 0019 19 0020 20 0021 21 0022 22 0023 23 0024 24 0025 25 0026 26 0027 27 0028 28 0029 29 0030 30 0031 31 0032 32 0033 33 0034 34 0035 35 0036 36 0037 37 0038 38 0039 39 0040 40 0041 41 0042 42 0043 43 0044 44 0045 45 0046 46 0047 47 0048 48 0049 49 0050 50 0051 51 0052 52 0053 53 0054 54 0055 55 0056 56 0057 57 0058 58 0059 59 0060 60 0061 61 0062 62 0063 63 0064 64 0065 65 0066 66 0067 67 0068 68 0069 69 0070 70 0071 71 0072 72 0073 73 0074 74 0075 75 0076 76 0077 77 0078 78 0079 79 0080 80 0081 81 0082 82 0083 83 0084 84 0085 85 0086 86 0087 87 0088 88 0089 89 0090 90 0091 91 0092 92 0093 93 0094 94 0095 95 0096 96 0097 97 0098 98 0099 99 or more persons FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). IPUMS Number of own children in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Number of own children under age 5 in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 or more own children under age 5 in household 98 One or more children have unknown age NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Age of eldest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. IPUMS Age of youngest own child in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 98 One or more children have unknown age 99 No own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. IPUMS Relationship to household head [general version] 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Relationship to household head [detailed version] 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2210 Civil union 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling's sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder, or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Age 000 Less than 1 year 001 1 year 002 2 years 003 3 004 4 005 5 006 6 007 7 008 8 009 9 010 10 011 11 012 12 013 13 014 14 015 15 016 16 017 17 018 18 019 19 020 20 021 21 022 22 023 23 024 24 025 25 026 26 027 27 028 28 029 29 030 30 031 31 032 32 033 33 034 34 035 35 036 36 037 37 038 38 039 39 040 40 041 41 042 42 043 43 044 44 045 45 046 46 047 47 048 48 049 49 050 50 051 51 052 52 053 53 054 54 055 55 056 56 057 57 058 58 059 59 060 60 061 61 062 62 063 63 064 64 065 65 066 66 067 67 068 68 069 69 070 70 071 71 072 72 073 73 074 74 075 75 076 76 077 77 078 78 079 79 080 80 081 81 082 82 083 83 084 84 085 85 086 86 087 87 088 88 089 89 090 90 091 91 092 92 093 93 094 94 095 95 096 96 097 97 098 98 099 99 100 100+ 999 Not reported/missing AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. IPUMS Age, grouped into intervals 01 0 to 4 02 5 to 9 03 10 to 14 04 15 to 19 05 0 to 5 06 6 to 10 07 10 to 15 08 11 to 14 09 15 to 17 10 16 to 19 11 18 to 24 12 20 to 24 13 25 to 29 14 30 to 34 15 35 to 39 16 40 to 44 17 45 to 49 18 50 to 54 19 55 to 59 20 60 to 64 21 65 to 69 22 70 to 74 23 75 to 79 24 80 to 84 25 85+ 98 Unknown AGE2 gives computed years of age grouped into intervals. IPUMS Sex 1 Male 2 Female 9 Unknown SEX reports the sex (gender) of the respondent. IPUMS Marital status [general version] NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. IPUMS Marital status [detailed version] 000 NIU (not in universe) 100 Single/never married 110 Engaged 111 Never married and never cohabited 200 Married or consensual union 210 Married, formally 211 Married, civil 212 Married, religious 213 Married, civil and religious 214 Married, civil or religious 215 Married, traditional/customary 216 Married, monogamous 217 Married, polygamous 219 Married, spouse absent (historical samples) 220 Consensual union 300 Separated/divorced/spouse absent 310 Separated or divorced 320 Separated or annulled 330 Separated 331 Separated legally 332 Separated de facto 333 Separated from marriage 334 Separated from consensual union 335 Separated from consensual union or marriage 340 Annulled 350 Divorced 400 Widowed 410 Widowed or divorced 411 Widowed from consensual union or marriage 412 Widowed from marriage 413 Widowed from consensual union 420 Widowed, divorced, or separated 999 Unknown/missing MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. IPUMS Age at first marriage or union 00 NIU (not in universe) 10 10 or younger 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 Unknown AGEMARR indicates the person's age at first marriage or consensual union. IPUMS Children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. IPUMS Children surviving 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHSURV reports the number of children born to a woman who were still living at the time of the census. IPUMS Number of female children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORNF indicates the number of female children ever born to a woman. Only live births are counted. IPUMS Number of male children ever born 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORNM indicates the number of male children ever born to a woman. Only live births are counted. IPUMS Number of female children surviving 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) CHSURVF indicates the number of female children ever born to a woman still living at the time of the census. IPUMS Number of male children surviving 00 No children 01 1 child 02 2 children 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) CHSURVM indicates the number of male children ever born to a woman still living at the time of the census. IPUMS Number of births last year None 1 1 (1 or more) 2 2 3 3 4 4+ 8 Unknown 9 NIU (not in universe) BIRTHSLYR indicates whether any -- and in most cases how many -- children were born to a woman in the past twelve months. IPUMS Children surviving from births last year 1 1 (1 or more) 2 2 3 3 4 4+ 8 Unknown 9 NIU (not in universe) BIRTHSURV indicates the number of children born in the past twelve months who were still living at the time of the census. IPUMS Number of children dead 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown/missing 99 NIU (not in universe) CHDEAD reports how many of the children ever born to a woman were no longer living at the time of the census. Women were to consider all live births by all fathers; they were to exclude still births. IPUMS Number of female children dead 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) CHDEADFEM indicates the number of female children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Female children ever born" and "Female children surviving" variables. That is not done in CHDEADFEM, which includes only the samples that directly reported the information in the appropriate form. IPUMS Number of male children dead 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) CHDEADMALE indicates the number of male children ever born to a woman who are no longer living. Stillbirths are not counted. It is possible to calculate total child deaths for samples that have both the "Male children ever born" and "Male children surviving" variables. That is not done in CHDEADMALE, which includes only the samples that directly reported the information in the appropriate form. IPUMS Mortality status of mother 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) MORTMOT indicates whether the person's biological mother was still living at the time of the census. IPUMS Mortality status of father 1 Alive 2 Dead 7 Does not know 8 Missing 9 NIU (not in universe) MORTFAT indicates whether the person's biological father was still living. IPUMS Number of own children in household 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) HOMECHILD indicates the number of surviving biological children living in the household with their mother (the respondent) at the time of the census. IPUMS Number of own female children in household 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 17 17 20 20+ 98 Unknown 99 NIU (not in universe) HOMEFEM indicates the number of female children born living in the household with their mother (the respondent). IPUMS Number of own male children in household 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) HOMEMALE indicates the number of male children born living in the household with their mother (the respondent). IPUMS Number of own children living elsewhere 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) AWAYCHILD indicates the number of surviving biological children not living in the household with their mother (the respondent) at the time of the census. IPUMS Number of own female children living elsewhere 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20+ 98 Unknown 99 NIU (not in universe) AWAYFEM indicates the number of surviving biological female children not living in the household with their mother (the respondent). IPUMS Number of own male children living elsewhere 00 None 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 98 Unknown 99 NIU (not in universe) AWAYMALE indicates the number of surviving biological male children not living in the household with their mother (the respondent). IPUMS Nativity status NIU (not in universe) 1 Native-born 2 Foreign-born 9 Unknown/missing NATIVITY indicates whether the person was native-born or foreign-born. IPUMS Citizenship 1 Citizen, not specified 2 Citizen by birth 3 Naturalized citizen 4 Not a citizen 5 Without citizenship, stateless 8 Unknown 9 NIU (not in universe) CITIZEN indicates the person's citizenship status within the country in which they were enumerated. IPUMS Country of citizenship 00000 NIU (not in universe) 10000 Africa 11000 Eastern Africa 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 South Sudan 11160 Uganda 11170 Tanzania 11180 Zambia 11190 Zimbabwe 11999 Eastern Africa, other or n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, other or n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt/United Arab Rep. 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, other or n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, other or n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15999 West Africa, other or n.s. 19999 Africa, other or n.s. 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21220 St. Lucia 21240 St. Vincent 21250 Trinidad and Tobago 21260 Turks and Caicos 21270 U.S. Virgin Islands 21999 Caribbean, other or n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, other or n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23999 South America, other or n.s. 24000 North America 24010 Bermuda 24020 Canada 24021 Canada, First Nations 24030 Greenland 24040 United States 24999 North America, other or n.s. 29999 Americas, other or n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, other or n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32990 Burma, India, Pakistan, Ceylon 32999 South-Central Asia, other or n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33991 Laos and Cambodia 33992 Malaysia and Singapore 33999 South-Eastern Asia, other or n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34051 Abkhazia 34052 South Ossetia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34991 Middle East 34999 Western Asia, other or n.s. 39999 Asia, other or n.s. 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41992 Central-Eastern Europe 41999 Eastern Europe, other or n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42121 Britain 42122 Scotland 42123 Wales 42990 Nordic countries 42999 Northern Europe, other or n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican City 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43999 Southern Europe, other or n.s. 44000 Western Europe 44010 Austria 44011 Austro-Hungarian 44020 Belgium 44022 Belgium/Netherlands/Luxemburg 44030 France 44040 Germany 44041 East Germany 44042 West Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44999 Western Europe, other or n.s. 49992 European Union 49993 European Union (Original 15) 49994 Other European Union 49999 Europe, other or n.s. 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, other or n.s. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, other or n.s. 55000 U.S. Pacific Possessions 55010 American Samoa 55020 Baker Island 55030 Guam 55040 Howland Island 55050 Johnston Atoll 55060 Kingman Reef 55070 Midway Islands 55080 Wake Island 55999 US Pacific, other or n.s. 59999 Oceania, other or n.s. 90000 Other countries n.s. 99998 No citizenship/nationality 99999 Unknown NATION indicates the person's country of citizenship. IPUMS State of birth, Sudan 11 Northern 12 Nahr El Nil 21 Red Sea 22 Kassala 23 Al Gedarif 31 Khartoum 41 Al Gezira 42 White Nile 43 Sinnar 44 Blue Nile 51 North Kordofan 52 South Kordofan 61 North Darfur 62 West Darfur 63 South Darfur 71 Upper Nile 72 Jonglei 73 Unity 81 Warrap 82 Northern Bahr El Ghazal 83 Western Bahr El Ghazal 84 Lakes 91 Western Equatoria 92 Central Equatoria 93 Eastern Equatoria 99 Abroad BPLSD indicates the person's state of birth in Sudan. Sudan and South Sudan were enumerated as one country in 2008. States of birth with South Sudan are also identified in this variable. IPUMS School attendance NIU (not in universe) 1 Yes 2 No, not specified 3 No, attended in the past 4 No, never attended 9 Unknown/missing SCHOOL indicates whether or not the person attended school at the time of the census or within some specified period of time prior to the census. IPUMS Literacy NIU (not in universe) 1 No, illiterate 2 Yes, literate 9 Unknown/missing LIT indicates whether or not the respondent could read and write in any language. A person is typically considered literate if he or she can both read and write. All other persons are illiterate, including those who can either read or write but cannot do both. IPUMS Educational attainment, international recode [general version] NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Educational attainment, international recode [detailed version] 000 NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Educational attainment, Sudan 00 NIU (not in universe) 10 None 11 Preschool 23 Primary less than grade 4 24 Primary grade 4 26 Primary grade 6 28 Primary grade 8 31 Junior secondary, 3 32 Junior secondary, 4 33 Secondary, grade 3 34 Secondary, grade 4 35 Secondary, grade 5 36 Secondary, grade 6 41 Post-secondary diploma 42 University first degree 51 Post-graduate diploma 52 Master's degree 53 Doctorate degree 99 Unknown EDUCSD indicates the person's educational attainment in Sudan in terms of the level of schooling and grade completed. IPUMS Activity status (employment status) [general version] NIU (not in universe) 1 Employed 2 Unemployed 3 Inactive 9 Unknown/missing EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". IPUMS Activity status (employment status) [detailed version] 000 NIU (not in universe) 100 Employed, not specified 110 At work 111 At work, and 'student' 112 At work, and 'housework' 113 At work, and 'seeking work' 114 At work, and 'retired' 115 At work, and 'no work' 116 At work, and other situation 117 At work, family holding, not specified 118 At work, family holding, not agricultural 119 At work, family holding, agricultural 120 Have job, not at work in reference period 130 Armed forces 131 Armed forces, at work 132 Armed forces, not at work in reference period 133 Military trainee 140 Marginally employed 200 Unemployed, not specified 201 Unemployed 6 or more months 202 Worked fewer than 6 months, permanent job 203 Worked fewer than 6 months, temporary job 210 Unemployed, experienced worker 220 Unemployed, new worker 230 No work available 240 Inactive unemployed 300 Inactive (not in labor force) 310 Housework 320 Unable to work, disabled or health reasons 321 Permanent disability 322 Temporary illness 323 Disabled or imprisoned 330 In school 340 Retirees and living on rent 341 Living on rents 342 Living on rents or pension 343 Retirees/pensioners 344 Retired 345 Pensioner 346 Non-retirement pension 347 Disability pension 348 Retired without benefits 350 Elderly 351 Elderly or disabled 360 Institutionalized 361 Prisoner 370 Intermittent worker 371 Not working, seasonal worker 372 Not working, occasional worker 380 Other income recipient 390 Inactive, other reasons 391 Too young to work 392 Dependent 999 Unknown/missing EMPSTAT indicates whether or not the respondent was part of the labor force -- working or seeking work -- over a specified period of time. Depending on the sample, EMPSTAT can also convey further information. The first digit of EMPSTAT is fully comparable, and classifies the population into three groups: employed, unemployed, and inactive. The combination of employed and unemployed yields the total labor force. The second and third digits of EMPSTAT preserve additional information available for some countries and census years but not for others. Employment status is sometimes referred to in other sources as "activity status". IPUMS Labor force participation 1 No, not in the labor force 2 Yes, in the labor force 8 Unknown 9 NIU (not in universe) LABFORCE is a dichotomous variable identifying whether a person participated in the labor force. Labor force participation generally means working or seeking work within a specified reference period. For most samples LABFORCE is a recode of EMPSTAT (employment status). A consistent lower age universe of 15 or older has been applied to increase comparability across samples. Full detail is retained in EMPSTAT, which should be used for any study of child labor. IPUMS Occupation, ISCO general 01 Legislators, senior officials and managers 02 Professionals 03 Technicians and associate professionals 04 Clerks 05 Service workers and shop and market sales 06 Skilled agricultural and fishery workers 07 Crafts and related trades workers 08 Plant and machine operators and assemblers 09 Elementary occupations 10 Armed forces 11 Other occupations, unspecified or n.e.c. 97 Response suppressed 98 Unknown 99 NIU (not in universe) OCCISCO records the person's primary occupation, coded according to the major categories in the International Standard Classification of Occupations (ISCO) scheme for 1988. For someone with more than one job, the primary occupation is typically the one in which the person had spent the most time or earned the most money. IPUMS Occupation, unrecoded OCC records the person's primary occupation, classified according to the system used by the respective national census office at the time. For someone with more than one job, the primary occupation is usually the one in which the person spent the most time or earned the most money, although this may not have been explicit in the instructions for a specific census. To ensure confidentiality, very small occupations are recoded to a residual category indicating the persons had an occupation, but the job title is not identified. The number of cases recoded should be too small to affect analyses. OCC is a 4-digit numeric variable. Some samples use fewer than 4 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. CodesArgentina 1970 - Spanish Argentina 1980 - Spanish Argentina 1991 - Spanish Argentina 2001 - Spanish Armenia 2011 Austria 1971-2001 - German Belarus 1999 - Russian Belarus 2009 Benin 1979 Benin 1992 Benin 2002 Benin 2013 Bolivia 1976 Bolivia 1992 Bolivia 2001 Bolivia 2012 Botswana 1981 Botswana 1991 Botswana 2001 Botswana 2011 Brazil 1960 - Portuguese Brazil 1970 - Portuguese Brazil 1980 - Portuguese Brazil 1991 - Portuguese Brazil 2000 - Portuguese Brazil 2010 Burkina Faso 1985 Burkina Faso 1996 Cambodia 1998 Cambodia 2004 Cambodia 2008 Cambodia 2013 Cambodia 2019 Cameroon 1976 Cameroon 2005 Canada 1971 Canada 1981-1991 Canada 2001 Canada 2011 Chile 1960 Chile 1970 Chile 1982 Chile 1992 Chile 2002 China 1982 China 1990 China 2000 Colombia 1964 Colombia 1973 - Spanish Costa Rica 1973 Costa Rica 1984 Costa Rica 2000 Costa Rica 2011 Cote d'Ivoire 1988 Cote d'Ivoire 1998 Cuba 2002 Cuba 2012 Denmark 1845 Denmark 1880 Denmark 1885 Dominican Republic 1960 Dominican Republic 1970 Dominican Republic 1981 Dominican Republic 2002 Dominican Republic 2010 Ecuador 1962 Ecuador 1974 Ecuador 1982 Ecuador 1990 Ecuador 2001 Ecuador 2010 Egypt 1986 Egypt 2006 El Salvador 1992 El Salvador 2007 Ethiopia 1984 Ethiopia 1994 Fiji 1976 Fiji 1986 Fiji 1996 Fiji 2007 Fiji 2014 Finland 2010 France 1962-1990 - French France 1999 France 2006 France 2011 Germany 1970 Germany 1981 Germany 1987 Ghana 1984 Ghana 2000 Ghana 2010 Greece 1971-1991 - Greek Greece 2001 - Greek Greece 2011 Guatemala 1964 Guatemala 1973 Guatemala 1981 Guatemala 1994 Guatemala 2002 Guinea 1983 Guinea 1996 Guinea 2014 Haiti 1982 Haiti 2003 Honduras 1961 Honduras 1974 Honduras 1988 Honduras 2001 Hungary 1970-1990 Hungary 2001 Hungary 2011 India 1983-2004 India 2009 Indonesia 1971 Indonesia 1976 Indonesia 1980 Indonesia 1985 Indonesia 1990 Indonesia 1995 Indonesia 2005 Iran 2006 Iran 2011 Iraq 1997 Ireland 1901 Ireland 1911 Ireland 1971 Ireland 1981 Ireland 1986 Ireland 1991 Ireland 1996 Ireland 2002 Ireland 2006 Ireland 2011 Ireland 2016 Israel 1972 Israel 1983 Israel 1995 Israel 2008 Italy 2001 Italy 2011 Italy Surveys 2011-2020 Jamaica 1982 Jamaica 1991 Jamaica 2001 Jordan 2004 Kenya 1989 Kyrgyz Republic 1999 Laos 1995 Lesotho 1996 Lesotho 2006 Liberia 1974 Liberia 2008 Malawi 1987 Malawi 1998 Malawi 2008 Malaysia 1970 Malaysia 1980-1991 Malaysia 2000 Mali 1987 Mali 1998 Mali 2009 Mauritius 1990 Mauritius 2000 Mauritius 2011 Mexico 1960 - Spanish Mexico 1970 - Spanish Mexico 1990 - Spanish Mexico 1995 - Spanish Mexico 2000 - Spanish Mexico 2010 Mexico 2015 Mexico 2020 Mexico Surveys 2005-2020 Mongolia 2000 Morocco 1982 Morocco 1994 Morocco 2004 Morocco 2014 Mozambique 1997 Mozambique 2007 Myanmar 2014 Nepal 2001 Nepal 2011 Netherlands 1960 Netherlands 1971 Netherlands 2001 Netherlands 2011 Nicaragua 1971 Nicaragua 1995 Nicaragua 2005 Nigeria 2008 Nigeria 2009 Nigeria 2010 Pakistan 1973 Palestine 1997 Palestine 2007 Palestine 2017 Panama 1960 - Spanish Panama 1970 - Spanish Panama 1980 - Spanish Panama 1990 - Spanish Panama 2000 - Spanish Panama 2010 Papua New Guinea 1980 Papua New Guinea 1990 Papua New Guinea 2000 Paraguay 1962 Paraguay 1972 Paraguay 1982 Paraguay 1992 Paraguay 2002 Peru 1993 Peru 2007 Peru 2017 Philippines 1990 Philippines 2000 Philippines 2010 Poland 1978 Poland 1988 Poland 2002 Portugal 1981 - Portuguese Portugal 1991 - Portuguese Portugal 2001 - Portuguese Portugal 2011 Puerto Rico 1970 Puerto Rico 1980 Puerto Rico 1990 Puerto Rico 2000-2005 Puerto Rico 2010 Puerto Rico 2015 Puerto Rico 2020 Romania 1977 Romania 1992 Romania 2002 Romania 2011 Rwanda 2002 - French Rwanda 2012 Saint Lucia 1991 Senegal 1988 Senegal 2002 Senegal 2013 Slovak Republic 1991 Slovak Republic 2001 Slovak Republic 2011 Sierra Leone 2004 Sierra Leone 2015 Slovenia 2002 South Africa 1996 South Africa 2001 South Africa 2007 South Sudan 2008 Spain 1981 - Spanish Spain 1991 - Spanish Spain 2001 - Spanish Spain 2011 Spain Surveys 2005-2020 Sudan 2008 Suriname 2004 Suriname 2012 Switzerland 1970 Switzerland 1980 Switzerland 1990 Switzerland 2000 Switzerland 2011 Tanzania 1988 Tanzania 2002 Tanzania 2012 Thailand 1970 Thailand 1980 Thailand 1990 Thailand 2000 Togo 1960 Togo 1970 Togo 2010 Trinidad and Tobago 1990 Trinidad and Tobago 2000 Trinidad and Tobago 2011 Turkey 1985 Turkey 1990 Turkey 2000 Uganda 1991 Uganda 2002 Uganda 2014 United Kingdom 1961 United Kingdom 1971 United Kingdom 1991 United Kingdom 2001 United States 1960 United States 1970 United States 1980 United States 1990 United States 2000-2005 United States 2010 United States 2015 United States 2020 Uruguay 1963 Uruguay 1975 Uruguay 1996 Uruguay 2006 Venezuela 1981 Venezuela 1990 Venezuela 2001 - Spanish Vietnam 1989 Vietnam 1999 Vietnam 2009 Vietnam 2019 Zambia 1990 Zambia 2000 Zambia 2010 Zimbabwe 2012 IPUMS Industry, general recode 000 NIU (not in universe) 010 Agriculture, fishing, and forestry 020 Mining and extraction 030 Manufacturing 040 Electricity, gas, water and waste management 050 Construction 060 Wholesale and retail trade 070 Hotels and restaurants 080 Transportation, storage, and communications 090 Financial services and insurance 100 Public administration and defense 110 Services, not specified 111 Business services and real estate 112 Education 113 Health and social work 114 Other services 120 Private household services 130 Other industry, n.e.c. 998 Response suppressed 999 Unknown INDGEN recodes the industrial classifications of the various samples into twelve groups that can be fairly consistently identified across all available samples. The groupings roughly conform to the International Standard Industrial Classification (ISIC). The third digit of INDGEN retains important detail among the service industries that could not be consistently distinguished in all samples. "Industry" refers to the activity or product of the establishment or sector in which a person worked. IPUMS Industry, unrecoded "Industry" refers to the activity or product of the establishment or sector in which the person worked. IND is classified according to the system used by the respective national census office at the time, and is not recoded by IPUMS-International. IND is a 5-digit numeric variable. Some samples use fewer than 5 digits. In those cases, the data are right-justified, and the extra leading digits are padded with zeroes. CodesArgentina 1970 - Spanish Argentina 1980 - Spanish Argentina 1991 - Spanish Argentina 2001 - Spanish Armenia 2001 Armenia 2011 Austria 1971-2001 - German Austria 2011 Bangladesh 1991 Bangladesh 2001 Bangladesh 2011 Belarus 2009 Benin 1979 Benin 1992 Benin 2002 Benin 2013 Bolivia 1976 Bolivia 1992 Bolivia 2001 Bolivia 2012 Botswana 1981 Botswana 1991 Botswana 2001 Botswana 2011 Brazil 1960 - Portuguese Brazil 1970 - Portuguese Brazil 1980 - Portuguese Brazil 1991 - Portuguese Brazil 2000 - Portuguese Brazil 2010 Burkina Faso 1996 Cambodia 1998 Cambodia 2004 Cambodia 2008 Cambodia 2013 Cambodia 2019 Cameroon 2005 Canada 1971 Canada 1981 Canada 1991-2001 Canada 2011 Chile 1960 Chile 1970 Chile 1982 Chile 1992 Chile 2002 Chile 2017 China 1982 China 1990 China 2000 Colombia 1964 - Spanish Colombia 1973 - Spanish Colombia 1993 - Spanish Colombia 2005 - Spanish Costa Rica 1963 Costa Rica 1973 Costa Rica 1984 Costa Rica 2000 Costa Rica 2011 Cote d’Ivoire 1988 Cote d’Ivoire 1998 Cuba 2002 Cuba 2012 Dominican Republic 1960 Dominican Republic 1970 Dominican Republic 1981 Dominican Republic 2002 Dominican Republic 2010 Ecuador 1962 Ecuador 1982 Ecuador 1990 Ecuador 2001 Ecuador 2010 Egypt 1986 Egypt 1996 Egypt 2006 El Salvador 1992 El Salvador 2007 Ethiopia 1984 Ethiopia 1994 Fiji 1966 Fiji 1976 Fiji 1986 Fiji 1996 Fiji 2007 Fiji 2014 Finland 2010 France 1962-1968 - French France 1975-1982 - French France 1990 - French France 1999 France 2006 France 2011 Germany 1970 Germany 1971 Germany 1981 Germany 1987 Ghana 1984 Ghana 2000 Ghana 2010 Greece 1971 Greece 1981 Greece 1991-2001 Greece 2011 Guatemala 1964 Guatemala 1973 Guatemala 1981 Guatemala 1994 Guatemala 2002 Guinea 1983 Guinea 2014 Haiti 1971 Haiti 1982 Haiti 2003 Honduras 1961 Honduras 1974 Honduras 2001 Hungary 2001 Hungary 2011 India 1983 India 1987 India 1993 India 1999 India 2004 India 2009 Indonesia 1971 Indonesia 1976 Indonesia 1980 Indonesia 1985 Indonesia 1990 Indonesia 1995 Indonesia 2000 Indonesia 2005 Indonesia 2010 Iran 2006 Iran 2011 Iraq 1997 Ireland 1971 Ireland 1981 Ireland 1986 Ireland 1991 Ireland 1996 Ireland 2002 Ireland 2006 Ireland 2011 Ireland 2016 Israel 1972 Israel 1983 Israel 1995 Israel 2008 Italy 2001 Italy 2011 Italy Surveys 2011-2013 Italy Surveys 2014-2020 Jamaica 1982 Jamaica 1991 Jamaica 2001 Jordan 2004 Kyrgyz Republic 1999 Kyrgyz Republic 2009 Laos 1995 Laos 2005 Laos 2015 Lesotho 2006 Liberia 1974 Liberia 2008 Malawi 1987 Malawi 1998 Malawi 2008 Malaysia 1970 Malaysia 1980-1991 Malaysia 2000 Mali 1987 Mali 1998 Mali 2009 Mauritius 1990 Mauritius 2000 Mauritius 2011 Mexico 1960 - Spanish Mexico 1970 - Spanish Mexico 1990 - Spanish Mexico 1995 - Spanish Mexico 2000 - Spanish Mexico 2010 Mexico 2015 Mexico 2020 Mexico surveys 2005-2019 Morocco 1982 Morocco 1994 Morocco 2004 Morocco 2014 Mozambique 1997 Mozambique 2007 Myanmar 2014 Nepal 2001 Nepal 2011 Netherlands 1960 Netherlands 1971 Netherlands 2001 Netherlands 2011 Nicaragua 1971 Nicaragua 1995 Nicaragua 2005 Nigeria 2006 Nigeria 2007 Nigeria 2008 Nigeria 2009 Nigeria 2010 Pakistan 1973 Palestine 1997 Palestine 2007 Palestine 2017 Panama 1960 - Spanish Panama 1970-1980 - Spanish Panama 1990-2000 - Spanish Panama 2010 Papua New Guinea 1980 Papua New Guinea 2000 Paraguay 1962 Paraguay 1972 Paraguay 1982 Paraguay 1992 Paraguay 2002 Peru 1993 Peru 2007 Peru 2017 Philippines 1990 Philippines 1995 Philippines 2000 Philippines 2010 Poland 1978 Poland 2002 Portugal 1981 - Portuguese Portugal 1991-2001 - Portuguese Portugal 2011 Puerto Rico 1970-2005 Puerto Rico 2010 Puerto Rico 2015 Puerto Rico 2020 Romania 1977 Romania 1992 Romania 2002 Romania 2011 Rwanda 2002 - French Rwanda 2012 Saint Lucia 1991 Senegal 1988 Senegal 2013 Sierra Leone 2004 South Africa 1996 South Africa 2001-2007 South Sudan 2008 Spain 1981 - Spanish Spain 1991 - Spanish Spain 2001 - Spanish Spain 2011 Spain Surveys 2005-2020 Sudan 2008 Suriname 2004 Suriname 2012 Switzerland 1970-2000 Switzerland 2011 Tanzania 2002 Tanzania 2012 Thailand 1970 Thailand 1980 Thailand 1990 Thailand 2000 Togo 1970 Togo 2010 Trinidad and Tobago 1980 Trinidad and Tobago 1990 Trinidad and Tobago 2000 Turkey 1985 Turkey 1990 Turkey 2000 Uganda 2002 United Kingdom 1961 United Kingdom 1971 United Kingdom 1991 United Kingdom 2001 United States 1960 United States 1970 United States 1980 United States 1990 United States 2000-2005 United States 2010 United States 2015 United States 2020 Uruguay 1963 Uruguay 1985 Uruguay 1996 Uruguay 2006 Venezuela 1981 Venezuela 1990 Venezuela 2001 - Spanish Vietnam 1989 Vietnam 1999 Vietnam 2009 Vietnam 2019 Zambia 1990 Zambia 2000 Zambia 2010 IPUMS Status in employment (class of worker) [general version] NIU (not in universe) 1 Self-employed 2 Wage/salary worker 3 Unpaid worker 4 Other 9 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Status in employment (class of worker) [detailed version] 000 NIU (not in universe) 100 Self-employed 101 Self-employed, unincorporated 102 Self-employed, incorporated 110 Employer 111 Sharecropper, employer 120 Working on own account 121 Own account, agriculture 122 Domestic worker, self-employed 123 Subsistence worker, own consumption 124 Own account, other 125 Own account, without temporary/unpaid help 126 Own account, with temporary/unpaid help 130 Member of cooperative 140 Sharecropper 141 Sharecropper, self-employed 142 Sharecropper, employee 150 Kibbutz member 199 Self-employed, not specified 200 Wage/salary worker 201 Management 202 Non-management 203 White collar (non-manual) 204 Blue collar (manual) 205 White or blue collar 206 Day laborer 207 Employee, with a permanent job 208 Employee, occasional, temporary, contract 209 Employee without legal contract 210 Wage/salary worker, private employer 211 Apprentice 212 Religious worker 213 Wage/salary worker, non-profit, NGO 214 White collar, private 215 Blue collar, private 216 Paid family worker 217 Cooperative employee 220 Wage/salary worker, government 221 Federal, government employee 222 State government employee 223 Local government employee 224 White collar, public 225 Blue collar, public 226 Public companies 227 Civil servants, local collectives 230 Domestic worker (work for private household) 240 Seasonal migrant 241 Seasonal migrant, no broker 242 Seasonal migrant, uses broker 250 Other wage and salary 251 Canal zone/commission employee 252 Government employment/training program 253 Mixed state/private enterprise/parastatal 254 Government public work program 255 State enterprise employee 256 Coordinated and continuous collaboration job 300 Unpaid worker 310 Unpaid family worker 320 Apprentice, unpaid or unspecified 330 Trainee 340 Apprentice or trainee 350 Works for others without wage 400 Other 999 Unknown/missing CLASSWK refers to the status of an economically active person with respect to his or her employment -- that is, the type of explicit or implicit contract of employment with other persons or organizations that the person has in his/her job. In general, the variable indicates whether a person was self-employed, or worked for someone else, either for pay or as an unpaid family worker. CLASSWK is related to EMPSTAT, which is used to define the universe in many samples. Class of worker is often referred to as "status in employment" in other sources. IPUMS Migration status, 1 year 00 NIU (not in universe) 10 Same major administrative unit 11 Same major, same minor administrative unit 12 Same major, different minor administrative unit 20 Different major administrative unit 30 Abroad 99 Unknown/missing MIGRATE1 indicates the person's place of residence 1 year ago. The first digit records movement across major administrative divisions and countries; the second digit reports movement across minor administrative divisions. IPUMS 1st subnational geographic level of residence 1 years prior to survey, world [consistent boundaries over time] 040011 Burgenland [State: Austria] 040012 Niederösterreich [State: Austria] 040013 Wien [State: Austria] 040021 Kärnten [State: Austria] 040022 Steiermark [State: Austria] 040031 Oberösterreich [State: Austria] 040032 Salzburg [State: Austria] 040033 Tirol [State: Austria] 040034 Vorarlberg [State: Austria] 040097 Foreign country [State: Austria] 040099 NIU [State: Austria] 854001 Boucle du Mouhoun [Region: Burkina Faso] 854002 Cascades [Region: Burkina Faso] 854003 Centre [Region: Burkina Faso] 854004 Centre-Est [Region: Burkina Faso] 854005 Centre-Nord [Region: Burkina Faso] 854006 Centre-Ouest [Region: Burkina Faso] 854007 Centre-Sud [Region: Burkina Faso] 854008 Est [Region: Burkina Faso] 854009 Hauts-Bassins [Region: Burkina Faso] 854010 Nord [Region: Burkina Faso] 854011 Plateau Central [Region: Burkina Faso] 854012 Sahel [Region: Burkina Faso] 854013 Sud-Ouest [Region: Burkina Faso] 854997 Abroad [Region: Burkina Faso] 854998 Unknown [Region: Burkina Faso] 854999 NIU [Region: Burkina Faso] 072001 Gaborone [District: Botswana] 072002 Francistown [District: Botswana] 072003 Lobatse [District: Botswana] 072004 Selebi Phikwe [District: Botswana] 072007 Central Tutume, Sowa [District: Botswana] 072010 Ngwaketse, Ngwaketse West, Ngwaketse Southern, Southern, Jwaneng [District: Botswana] 072011 Borolong [District: Botswana] 072020 South East [District: Botswana] 072030 Kweneng, Kweneng South, Kweneng North [District: Botswana] 072040 Kgatleng [District: Botswana] 072050 Central Serowe/Palapye [District: Botswana] 072051 Central Mahalapye [District: Botswana] 072052 Central Bobonong [District: Botswana] 072053 Central Boteti, Orapa [District: Botswana] 072060 North East [District: Botswana] 072070 Ngamiland East [District: Botswana] 072071 Ngamiland West, Delta [District: Botswana] 072072 Chobe [District: Botswana] 072080 Ghanzi, Central Kgalagadi Game Reserve (CKGR) [District: Botswana] 072090 Tshabong (Kgalagadi South) [District: Botswana] 072091 Hukunsti (Kgalagadi North) [District: Botswana] 072092 Botswana, district unknown [District: Botswana] 072097 Abroad [District: Botswana] 072098 Unknown [District: Botswana] 072099 NIU (not in universe) [District: Botswana] 124010 Newfoundland and Labrador [Province: Canada] 124011 Prince Edward Island, Yukon Territory, Northwest Territories, Nunavut [Province: Canada] 124012 Nova Scotia [Province: Canada] 124013 New Brunswick [Province: Canada] 124024 Quebec [Province: Canada] 124035 Ontario [Province: Canada] 124046 Manitoba [Province: Canada] 124047 Saskatchewan [Province: Canada] 124048 Alberta [Province: Canada] 124059 British Columbia [Province: Canada] 124098 Unknown [Province: Canada] 124099 NIU (not in universe) [Province: Canada] 384001 Lagunes, Sud Comoé, Sud Bandama, Agneby [Region: Cote D'Ivoire] 384002 Haut Sassandra, Marahoué, Fromager [Region: Cote D'Ivoire] 384003 Savanes [Region: Cote D'Ivoire] 384004 Vallée du Bandam, Lacs, N'Zi Comoé [Region: Cote D'Ivoire] 384005 Moyen Comoé [Region: Cote D'Ivoire] 384006 Montagnes, Moyen Cavally [Region: Cote D'Ivoire] 384008 Zanzan [Region: Cote D'Ivoire] 384009 Bas Sassandra [Region: Cote D'Ivoire] 384010 Denguele, Worodougou, Bafing [Region: Cote D'Ivoire] 384097 Abroad [Region: Cote D'Ivoire] 384098 Unknown [Region: Cote D'Ivoire] 384099 NIU [Region: Cote D'Ivoire] 300001 Etolia and Akarnania [Department: Greece] 300003 Viotia [Department: Greece] 300004 Evia [Department: Greece] 300005 Evrytania [Department: Greece] 300006 Fthiotida [Department: Greece] 300007 Fokida [Department: Greece] 300011 Argolida [Department: Greece] 300012 Arkadia [Department: Greece] 300013 Achaia [Department: Greece] 300014 Ilia [Department: Greece] 300015 Korinthia [Department: Greece] 300016 Lakonia [Department: Greece] 300017 Messinia [Department: Greece] 300021 Zakynthos [Department: Greece] 300022 Kerkyra [Department: Greece] 300023 Kefallinia [Department: Greece] 300024 Lefkada [Department: Greece] 300031 Arta [Department: Greece] 300032 Thesprotia [Department: Greece] 300033 Ioannina [Department: Greece] 300034 Preveza [Department: Greece] 300041 Karditsa [Department: Greece] 300042 Larissa [Department: Greece] 300043 Magnissia [Department: Greece] 300044 Trikala [Department: Greece] 300051 Grevena [Department: Greece] 300052 Drama [Department: Greece] 300053 Imathia [Department: Greece] 300054 Thessaloniki [Department: Greece] 300055 Kavala [Department: Greece] 300056 Kastoria [Department: Greece] 300057 Kilkis [Department: Greece] 300058 Kozani [Department: Greece] 300059 Pella [Department: Greece] 300061 Pieria [Department: Greece] 300062 Serres [Department: Greece] 300063 Florina [Department: Greece] 300064 Chalkidiki and Agion Oros [Department: Greece] 300071 Evros [Department: Greece] 300072 Xanthi [Department: Greece] 300073 Rodopi [Department: Greece] 300081 Dodekanissos [Department: Greece] 300082 Kyklades [Department: Greece] 300083 Lesvos [Department: Greece] 300084 Samos [Department: Greece] 300085 Chios [Department: Greece] 300091 Iraklio [Department: Greece] 300092 Lassithi [Department: Greece] 300093 Rethymno [Department: Greece] 300094 Chania [Department: Greece] 300101 Prefecture of Athens [Department: Greece] 300102 Prefecture of East Attiki [Department: Greece] 300103 Prefecture of West Attiki [Department: Greece] 300104 Prefecture of Pireas [Department: Greece] 300996 Foreign country [Department: Greece] 300997 Response suppressed [Department: Greece] 300998 Unknown [Department: Greece] 300999 NIU (not in universe) [Department: Greece] 372001 Dublin [Region: Ireland] 372002 Midlands [Region: Ireland] 372003 Mid-East, Border [Region: Ireland] 372004 Mid-West, South-East [Region: Ireland] 372006 West [Region: Ireland] 372008 South West [Region: Ireland] 372096 Ireland, region not specified [Region: Ireland] 372097 Abroad [Region: Ireland] 372098 Unknown [Region: Ireland] 372099 NIU (not in universe) [Region: Ireland] 380001 Piemonte, Valle d'Aosta [Region: Italy] 380003 Lombardia [Region: Italy] 380004 Trentino Alto Adige [Region: Italy] 380005 Veneto [Region: Italy] 380006 Friuli Venezia Giulia [Region: Italy] 380007 Liguria [Region: Italy] 380008 Emilia Romagna, Marche [Region: Italy] 380009 Toscana [Region: Italy] 380010 Umbria [Region: Italy] 380012 Lazio [Region: Italy] 380013 Abruzzo [Region: Italy] 380014 Molise [Region: Italy] 380015 Campania [Region: Italy] 380016 Puglia [Region: Italy] 380017 Basilicata [Region: Italy] 380018 Calabria [Region: Italy] 380019 Sicilia [Region: Italy] 380020 Sardegna [Region: Italy] 380097 Foregin Country [Region: Italy] 380099 NIU [Region: Italy] 404001 Nairobi [Province: Kenya] 404002 Central [Province: Kenya] 404003 Coast [Province: Kenya] 404004 Eastern [Province: Kenya] 404005 Northeastern [Province: Kenya] 404006 Nyanza [Province: Kenya] 404007 Rift Valley [Province: Kenya] 404008 Western [Province: Kenya] 404097 Abroad [Province: Kenya] 404098 Unknown [Province: Kenya] 404099 NIU (not in universe) [Province: Kenya] 454101 Chitipa [District: Malawi] 454102 Karonga [District: Malawi] 454103 Nkhata Bay, Likoma [District: Malawi] 454104 Rumphi [District: Malawi] 454105 Mzimba, Mzuzu city [District: Malawi] 454201 Kasungu [District: Malawi] 454202 Nkhotakota [District: Malawi] 454203 Ntchisi [District: Malawi] 454204 Dowa [District: Malawi] 454205 Salima [District: Malawi] 454206 Lilongwe, Lilongwe city [District: Malawi] 454207 Mchinji [District: Malawi] 454208 Dedza [District: Malawi] 454209 Ntcheu [District: Malawi] 454301 Mangochi [District: Malawi] 454302 Machinga [District: Malawi] 454303 Zomba, Zomba city [District: Malawi] 454304 Chiradzulu [District: Malawi] 454305 Blantyre, Blantyre city [District: Malawi] 454307 Thyolo [District: Malawi] 454308 Mulanje [District: Malawi] 454309 Phalombe [District: Malawi] 454310 Chikwawa [District: Malawi] 454311 Nsanje [District: Malawi] 454312 Balaka [District: Malawi] 454313 Mwanza, Neno [District: Malawi] 454997 Abroad [District: Malawi] 454998 Unknown [District: Malawi] 454999 NIU (not in universe) [District: Malawi] 508001 Niassa [Province: Mozambique] 508002 Cabo Delgado [Province: Mozambique] 508003 Nampula [Province: Mozambique] 508004 Zambézia [Province: Mozambique] 508005 Tete [Province: Mozambique] 508006 Manica [Province: Mozambique] 508007 Sofala [Province: Mozambique] 508008 Inhambane [Province: Mozambique] 508009 Gaza [Province: Mozambique] 508010 Maputo province [Province: Mozambique] 508011 Maputo city [Province: Mozambique] 508097 Foreign Country [Province: Mozambique] 508098 Unknown [Province: Mozambique] 508099 NIU (not in universe) [Province: Mozambique] 598001 Western [Province: Papua New Guinea] 598002 Gulf [Province: Papua New Guinea] 598003 Central [Province: Papua New Guinea] 598004 National Capital District [Province: Papua New Guinea] 598005 Milne Bay [Province: Papua New Guinea] 598006 Northern [Province: Papua New Guinea] 598007 Southern Highlands, Hela [Province: Papua New Guinea] 598008 Enga [Province: Papua New Guinea] 598009 Western Highlands, Jiwaka [Province: Papua New Guinea] 598010 Chimbu [Province: Papua New Guinea] 598011 Eastern Highlands [Province: Papua New Guinea] 598012 Morobe [Province: Papua New Guinea] 598013 Madang [Province: Papua New Guinea] 598014 East Sepik [Province: Papua New Guinea] 598015 West Sepik [Province: Papua New Guinea] 598016 Manus [Province: Papua New Guinea] 598017 New Ireland [Province: Papua New Guinea] 598018 East New Britain [Province: Papua New Guinea] 598019 West New Britain [Province: Papua New Guinea] 598020 Autonomous Region of Bougainville [Province: Papua New Guinea] 598097 Foreign country [Province: Papua New Guinea] 598098 Unknown [Province: Papua New Guinea] 598099 NIU (not in universe) [Province: Papua New Guinea] 616002 Dolnośląskie [Vovoidship (Province): Poland] 616004 Kujawsko pomorskie [Vovoidship (Province): Poland] 616006 Lubelskie [Vovoidship (Province): Poland] 616008 Lubuskie [Vovoidship (Province): Poland] 616010 Łódzkie [Vovoidship (Province): Poland] 616012 Małopolskie [Vovoidship (Province): Poland] 616014 Mazowieckie [Vovoidship (Province): Poland] 616016 Opolskie [Vovoidship (Province): Poland] 616018 Podkarpackie [Vovoidship (Province): Poland] 616020 Podlaskie [Vovoidship (Province): Poland] 616022 Pomorskie [Vovoidship (Province): Poland] 616024 Śląskie [Vovoidship (Province): Poland] 616026 Świętokrzyskie [Vovoidship (Province): Poland] 616028 Warmińsko mazurskie [Vovoidship (Province): Poland] 616030 Wielkopolskie [Vovoidship (Province): Poland] 616032 Zachodniopomorskie [Vovoidship (Province): Poland] 616098 Unknown [Vovoidship (Province): Poland] 616099 NIU (not in universe) [Vovoidship (Province): Poland] 620111 Minho-Lima [Subregion: Portugal] 620112 Cávado [Subregion: Portugal] 620113 Ave [Subregion: Portugal] 620114 Grande Porto [Subregion: Portugal] 620115 Tâmega [Subregion: Portugal] 620116 Entre Douro e Vouga [Subregion: Portugal] 620117 Douro [Subregion: Portugal] 620118 Alto Trás-os-Montes [Subregion: Portugal] 620150 Algarve [Subregion: Portugal] 620161 Baixo Vouga [Subregion: Portugal] 620162 Baixo Mondego [Subregion: Portugal] 620163 Pinhal Litoral [Subregion: Portugal] 620165 Dão-Lafões [Subregion: Portugal] 620166 Oeste [Subregion: Portugal] 620167 Médio Tejo [Subregion: Portugal] 620169 Other Center [Subregion: Portugal] 620171 Grande Lisboa [Subregion: Portugal] 620172 Península de Setúbal [Subregion: Portugal] 620185 Lezíria do Tejo [Subregion: Portugal] 620189 Other Alentejo [Subregion: Portugal] 620200 Região Autónoma dos Açores [Subregion: Portugal] 620300 Região Autónoma da Madeira [Subregion: Portugal] 620998 Foreign country [Subregion: Portugal] 620999 NIU (not in universe) [Subregion: Portugal] 643001 Altai Krai [Region: Russia] 643003 Krasnodar Krai [Region: Russia] 643004 Krasnoyarsk Krai [Region: Russia] 643005 Primorsky Krai [Region: Russia] 643007 Stavropol Krai [Region: Russia] 643008 Khabarovsk Krai [Region: Russia] 643010 Amur Oblast [Region: Russia] 643011 Arkhangelsk Oblast [Region: Russia] 643012 Astrakhan Oblast [Region: Russia] 643013 Nenets Autonomous District 643014 Belgorod Oblast [Region: Russia] 643015 Bryansk Oblast [Region: Russia] 643017 Vladimir Oblast [Region: Russia] 643018 Volgograd Oblast [Region: Russia] 643019 Vologda Oblast [Region: Russia] 643020 Voronezh Oblast [Region: Russia] 643022 Nizhny Novgorod Oblast [Region: Russia] 643024 Ivanovo Oblast [Region: Russia] 643025 Irkutsk Oblast [Region: Russia] 643026 Republic of Ingushetia [Region: Russia] 643027 Kaliningrad Oblast [Region: Russia] 643028 Tver Oblast [Region: Russia] 643029 Kaluga Oblast [Region: Russia] 643030 Kamchatka Krai [Region: Russia] 643032 Kemerovo Oblast [Region: Russia] 643033 Kirov Oblast [Region: Russia] 643034 Kostroma Oblast [Region: Russia] 643036 Samara Oblast [Region: Russia] 643037 Kurgan Oblast [Region: Russia] 643038 Kursk Oblast [Region: Russia] 643040 City of Federal Importance St. Petersburg [Region: Russia] 643041 Leningrad Oblast [Region: Russia] 643042 Lipetsk Oblast [Region: Russia] 643044 Magadan Oblast [Region: Russia] 643045 City of Federal Importance Moscow [Region: Russia] 643046 Moscow Oblast [Region: Russia] 643047 Murmansk Oblast [Region: Russia] 643049 Novgorod Oblast [Region: Russia] 643050 Novosibirsk Oblast [Region: Russia] 643052 Omsk Oblast [Region: Russia] 643053 Orenburg Oblast [Region: Russia] 643054 Oryol Oblast [Region: Russia] 643056 Penza Oblast [Region: Russia] 643057 Perm Krai [Region: Russia] 643058 Pskov Oblast [Region: Russia] 643060 Rostov Oblast [Region: Russia] 643061 Ryazan Oblast [Region: Russia] 643063 Saratov Oblast [Region: Russia] 643064 Sakhalin Oblast [Region: Russia] 643065 Sverdlovsk Oblast [Region: Russia] 643066 Smolensk Oblast [Region: Russia] 643068 Tambov Oblast [Region: Russia] 643069 Tomsk Oblast [Region: Russia] 643070 Tula Oblast [Region: Russia] 643071 Tyumen Oblast [Region: Russia] 643072 Khanty-Mansi Autonomous District - Yugra [Region: Russia] 643073 Ulyanovsk Oblast [Region: Russia] 643074 Yamalo-Nenets Autonomous District [Region: Russia] 643075 Chelyabinsk Oblast [Region: Russia] 643076 Zabaykalsky Krai, Aginsky Buryat District [Region: Russia] 643077 Chukotka Autonomous Region [Region: Russia] 643078 Yaroslavskaya Oblast [Region: Russia] 643079 Republic of Adygea [Region: Russia] 643080 Republic of Bashkortostan [Region: Russia] 643081 Republic of Buryatia [Region: Russia] 643082 Republic of Dagestan [Region: Russia] 643083 Kabardino-Balkaria Republic [Region: Russia] 643084 Altai Republic [Region: Russia] 643085 Republic of Kalmykia [Region: Russia] 643086 Republic of Karelia [Region: Russia] 643087 Komi Republic [Region: Russia] 643088 Mari El Republic [Region: Russia] 643089 Republic of Mordovia [Region: Russia] 643090 Republic of North Ossetia-Alania [Region: Russia] 643091 Karachay-Cherkess Republic [Region: Russia] 643092 Republic of Tatarstan [Region: Russia] 643093 Tyva Republic [Region: Russia] 643094 Udmurtia Republic [Region: Russia] 643095 Republic of Khakassia [Region: Russia] 643096 Chechen Republic [Region: Russia] 643097 Chuvash Republic [Region: Russia] 643098 Republic of Sakha (Yakutia) [Region: Russia] 643099 Jewish Autonomous Region [Region: Russia] 643997 Foreign Country [Region: Russia] 643998 Unknown [Region: Russia] 643999 NIU [Region: Russia] 686001 Dakar [Region: Senegal] 686002 Ziguinchor [Region: Senegal] 686003 Diourbel [Region: Senegal] 686004 Saint Louis, Louga, Matam [Region: Senegal] 686005 Tambacounda, Kedougou [Region: Senegal] 686006 Kaolack, Fatick, Kaffrine [Region: Senegal] 686007 Thiès [Region: Senegal] 686010 Kolda, Sedhiou [Region: Senegal] 686097 Abroad [Region: Senegal] 686099 NIU (not in universe) [Region: Senegal] 724011 Galicia [Communities & autonomous city: Spain] 724012 Principado de Asturias [Communities & autonomous city: Spain] 724013 Cantabria [Communities & autonomous city: Spain] 724021 País Vasco [Communities & autonomous city: Spain] 724022 Comunidad Foral de Navarra [Communities & autonomous city: Spain] 724023 La Rioja [Communities & autonomous city: Spain] 724024 Aragón [Communities & autonomous city: Spain] 724030 Comunidad de Madrid [Communities & autonomous city: Spain] 724041 Castilla y León [Communities & autonomous city: Spain] 724042 Castilla-La Mancha [Communities & autonomous city: Spain] 724043 Extremadura [Communities & autonomous city: Spain] 724051 Cataluña [Communities & autonomous city: Spain] 724052 Comunidad Valenciana [Communities & autonomous city: Spain] 724053 Islas Baleares [Communities & autonomous city: Spain] 724061 Andalucía [Communities & autonomous city: Spain] 724062 Región de Murcia [Communities & autonomous city: Spain] 724063 Ciudad Autónoma de Ceuta [Communities & autonomous city: Spain] 724064 Ciudad Autónoma de Melilla [Communities & autonomous city: Spain] 724070 Canarias [Communities & autonomous city: Spain] 724097 Foreign country [Communities & autonomous city: Spain] 724999 NIU (not in universe) [Communities & autonomous city: Spain] 728011 Northern [State:South Sudan] 728012 Nahr El Nil [State:South Sudan] 728021 Red Sea [State:South Sudan] 728022 Kassala [State:South Sudan] 728023 Al Gedarif [State:South Sudan] 728031 Khartoum [State:South Sudan] 728041 Al Gezira [State:South Sudan] 728042 White Nile [State:South Sudan] 728043 Sinnar [State:South Sudan] 728044 Blue Nile [State:South Sudan] 728051 North Kordofan [State:South Sudan] 728052 South Kordofan [State:South Sudan] 728061 North Darfur [State:South Sudan] 728062 West Darfur [State:South Sudan] 728063 South Darfur [State:South Sudan] 728071 Upper Nile [State: South Sudan] 728072 Jonglei [State: South Sudan] 728073 Unity [State: South Sudan] 728081 Warrap [State: South Sudan] 728082 Northern Bahr El Ghazal [State: South Sudan] 728083 Western Bahr El Ghazal [State: South Sudan] 728084 Lakes [State: South Sudan] 728091 Western Equatoria [State: South Sudan] 728092 Central Equatoria [State: South Sudan] 728093 Eastern Equatoria [State: South Sudan] 728098 Abroad [State: South Sudan] 728099 NIU (Not in universe) [State: South Sudan] 729011 Northern [State: Sudan] 729012 Nahr El Nil [State: Sudan] 729021 Red Sea [State: Sudan] 729022 Kassala [State: Sudan] 729023 Al Gedarif [State: Sudan] 729031 Khartoum [State: Sudan] 729041 Al Gezira [State: Sudan] 729042 White Nile [State: Sudan] 729043 Sinnar [State: Sudan] 729044 Blue Nile [State: Sudan] 729051 North Kordofan [State: Sudan] 729052 South Kordofan [State: Sudan] 729061 North Darfur [State: Sudan] 729062 West Darfur [State: Sudan] 729063 South Darfur [State: Sudan] 729071 Upper Nile [State: Sudan] 729072 Jonglei [State: Sudan] 729073 Unity [State: Sudan] 729081 Warrap [State: Sudan] 729082 Northern Bahr El Ghazal [State: Sudan] 729083 Western Bahr El Ghazal [State: Sudan] 729084 Lakes [State: Sudan] 729091 Western Equatoria [State: Sudan] 729092 Central Equatoria [State: Sudan] 729093 Eastern Equatoria [State: Sudan] 729098 Abroad [State: Sudan] 780010 Port of Spain [Region: Trinidad and Tobago] 780020 San Fernando [Region: Trinidad and Tobago] 780080 Diego Martin, San Juan/Laventille, Tunapuna/Piarco, Chaguanas, Sangre Grande, Couva/Tabaquite /Talparo, Rio Claro/Mayaro, Siparia, Penal/Debe, Princess Town, Port Fontin, Caroni, St. Andrew/St. David, Victoria, St. Patrick, Arima [Region: Trinidad and Tobago] 780094 St. Paul, St. Mary, St. David, St. George, St. Patrick, St. Andrew, St. John, Tobago [Region: Trinidad and Tobago] 780098 Unknown [Region: Trinidad and Tobago] 780099 NIU (not in universe) [Region: Trinidad and Tobago] 826101 North East [Region: United Kingdom] 826102 North West [Region: United Kingdom] 826103 Yorkshire and the Humber [Region: United Kingdom] 826104 East Midlands [Region: United Kingdom] 826105 West Midlands [Region: United Kingdom] 826106 East of England [Region: United Kingdom] 826107 South East [Region: United Kingdom] 826108 South West [Region: United Kingdom] 826110 Outer London, Inner London [Region: United Kingdom] 826111 Scotland [Region: United Kingdom] 826112 Wales [Region: United Kingdom] 826113 Northern Ireland [Region: United Kingdom] 826197 Other country [Region: United Kingdom] 826198 Unknown [Region: United Kingdom] 826199 NIU (not in universe) [Region: United Kingdom] 834001 Dodoma [Region: Tanzania] 834002 Arusha, Manyara [Region: Tanzania] 834003 Kilimanjaro [Region: Tanzania] 834004 Tanga [Region: Tanzania] 834005 Morogoro [Region: Tanzania] 834006 Pwani [Region: Tanzania] 834007 Dar es Salaam [Region: Tanzania] 834008 Lindi [Region: Tanzania] 834009 Mtwara [Region: Tanzania] 834010 Ruvuma [Region: Tanzania] 834011 Iringa, Njombe [Region: Tanzania] 834012 Mbeya [Region: Tanzania] 834013 Singida [Region: Tanzania] 834014 Tabora [Region: Tanzania] 834015 Katavi, Rukwa [Region: Tanzania] 834016 Kigoma [Region: Tanzania] 834019 Geita, Kagera, Mwanza, Shinyanga, Simiyu [Region: Tanzania] 834020 Mara [Region: Tanzania] 834051 Zanzibar North [Region: Tanzania] 834052 Zanzibar South [Region: Tanzania] 834053 Zanzibar Town/West [Region: Tanzania] 834054 Pemba North [Region: Tanzania] 834055 Pemba South [Region: Tanzania] 834097 Abroad [Region: Tanzania] 834098 Unknown [Region: Tanzania] 834099 NIU (not in universe) [Region: Tanzania] 840001 Alabama [State: United States] 840002 Alaska [State: United States] 840004 Arizona [State: United States] 840005 Arkansas [State: United States] 840006 California [State: United States] 840008 Colorado [State: United States] 840009 Connecticut [State: United States] 840010 Delaware [State: United States] 840011 District of Columbia [State: United States] 840012 Florida [State: United States] 840013 Georgia [State: United States] 840015 Hawaii [State: United States] 840016 Idaho [State: United States] 840017 Illinois [State: United States] 840018 Indiana [State: United States] 840019 Iowa [State: United States] 840020 Kansas [State: United States] 840021 Kentucky [State: United States] 840022 Louisiana [State: United States] 840023 Maine [State: United States] 840024 Maryland [State: United States] 840025 Massachusetts [State: United States] 840026 Michigan [State: United States] 840027 Minnesota [State: United States] 840028 Mississippi [State: United States] 840029 Missouri [State: United States] 840030 Montana [State: United States] 840031 Nebraska [State: United States] 840032 Nevada [State: United States] 840033 New Hampshire [State: United States] 840034 New Jersey [State: United States] 840035 New Mexico [State: United States] 840036 New York [State: United States] 840037 North Carolina [State: United States] 840038 North Dakota [State: United States] 840039 Ohio [State: United States] 840040 Oklahoma [State: United States] 840041 Oregon [State: United States] 840042 Pennsylvania [State: United States] 840044 Rhode Island [State: United States] 840045 South Carolina [State: United States] 840046 South Dakota [State: United States] 840047 Tennessee [State: United States] 840048 Texas [State: United States] 840049 Utah [State: United States] 840050 Vermont [State: United States] 840051 Virginia [State: United States] 840053 Washington [State: United States] 840054 West Virginia [State: United States] 840055 Wisconsin [State: United States] 840056 Wyoming [State: United States] 840097 Abroad [State: United States] 840999 NIU (not in universe) [State: United States] 894001 Central [Province: Zambia] 894002 Copperbelt [Province: Zambia] 894003 Eastern, Muchinga, Northern [Province: Zambia] 894004 Luapula [Province: Zambia] 894005 Lusaka [Province: Zambia] 894008 North Western [Province: Zambia] 894009 Southern [Province: Zambia] 894010 Western [Province: Zambia] 894097 Foreign country [Province: Zambia] 894098 Unknown [Province: Zambia] 894099 NIU (not in universe) [Province: Zambia] GEOMIG1_1 indicates the major administrative unit in which the person resided one year prior to the survey. Only intra-national migrations are recorded; however, the variable incorporates geographies for every country that lists place of residence one year ago, to enable comparative analysis of subnational migration. Foreign migrants are coded 097 or 997. Codes for GEOMIG1_1 match the geographic codes in GEOLEV1 (current place of residence). For similar information for different time intervals since migration, see variables GEOMIG1_P, GEOMIG1_5, and GEOMIG1_10. More on migration and geography can be found here. IPUMS Years residing in current locality 00 Less than 1 year 01 1 year (or 1 year or less) 02 2 years 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95+ years 96 Less than 5 years 97 More than 5 years 98 Unknown 99 NIU (not in universe) MIGYRS1 indicates how many years the person has resided in their current locality of residence. IPUMS State of residence 1 year ago, Sudan; consistent boundaries, GIS 729011 Northern 729012 Nahr El Nil 729021 Red Sea 729022 Kassala 729023 Al Gedarif 729031 Khartoum 729041 Al Gezira 729042 White Nile 729043 Sinnar 729044 Blue Nile 729051 North Kordofan 729052 South Kordofan 729061 North Darfur 729062 West Darfur 729063 South Darfur 729071 Upper Nile 729072 Jonglei 729073 Unity 729081 Warrap 729082 Northern Bahr El Ghazal 729083 Western Bahr El Ghazal 729084 Lakes 729091 Western Equatoria 729092 Central Equatoria 729093 Eastern Equatoria 729098 Abroad MIG1_1_SD indicates the person's state of residence one year ago within Sudan. Presumably, infants are recorded where one of their parents resided one year ago. Sudan and South Sudan were enumerated as one country in 2008. Enumerated states of residence 1 year ago within South Sudan are also included in this variable. Click on the Source Variables tab for information on place of residence for each sample year. Source variables may contain more geographic unit detail but are not suitable for cross-temporal comparison. IPUMS Disability status NIU (not in universe) 1 Yes, disabled 2 No, not disabled 9 Unknown DISABLED indicates whether the person reported a disability of any kind. IPUMS Employment disability 1 Disabled 2 Not disabled 8 Unknown 9 NIU (not in universe) DISEMP indicates if the respondent was economically inactive because of disabilities or, in some instances, other health-related reasons. IPUMS Blind or vision-impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISBLND indicates whether the person was blind or had limited vision. IPUMS Deaf or hearing-impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISDEAF indicates whether the person was deaf or had limited hearing. IPUMS Mute or speech impaired NIU (not in universe) 1 Yes 2 No 9 Unknown DISMUTE indicates if the person could not speak or had a significant speech impediment. IPUMS Disability affecting lower extremities NIU (not in universe) 1 Yes 2 No 9 Unknown DISLOWR indicates whether the person lacked use of one or both legs. IPUMS Disability affecting upper extremities NIU (not in universe) 1 Yes 2 No 9 Unknown DISUPPR indicates whether the person lacked full use of at least one arm or hand. IPUMS Mental disability NIU (not in universe) 1 Yes 2 No 9 Unknown DISMNTL indicates whether the person suffered a mental disability in the form of diminished capacity. IPUMS Person number (within household) Sudan 2008: All persons 00 Household record 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 This variable indicates the person number (within household). IPUMS Relationship <svar a="all" v="SD08A404 SD08A504">2. What is the relationship of [the respondent] to the head of household?<br /><div class="i1">[] 1 Head<br />[] 2 Spouse<br />[] 3 Son / daughter<br />[] 4 Wife of son / husband of daughter<br />[] 5 Grandchild<br />[] 6 Niece / nephew<br />[] 7 Parent / parent-in-law<br />[] 8 Sister / brother-in-laws<br />[] 9 Other relative<br />[] 10 Non relative</div><br /></svar> Sudan 2008: All persons 01 Head 02 Spouse 03 Daughter/son 04 Spouse of son/daughter 05 Grandchild 06 Niece/nephew 07 Parent/parent in-law 08 Sibling/sibling-in-law 09 Other relative 10 Non-relative This variable indicates the person's relationship to the head of household. IPUMS Sex <svar a="all" v="SD08A405 SD08A505">3. Is [the respondent] male or female?<br /><div class="i1">[] 1 Male<br />[] 2 Female</div><br /></svar> Sudan 2008: All persons 1 Male 2 Female This variable indicates the person's sex. IPUMS Age <svar a="all" v="SD08A406 SD08A506">4. What is [the respondent's] age in completed years?<br /><div class="i1">If less than one year, code "0", if over 95, code "95".<br />_ _</div><br /></svar> Sudan 2008: All persons 00 Less than 1 years old 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 years and above This variable indicates the person's age in completed years. IPUMS Nationality <svar a="all" v="SD08A407 SD08A507">5. What is [the respondent's] nationality?<br /><div class="i1">Use the nationality codes on the separate sheet<br />_ _</div><br /></svar> Sudan 2008: All persons 01 Sudanese 02 Egyptian 03 Libyan 04 Eritrean 05 Ethiopian 06 Ugandan 07 Kenyan 08 Congolese - DRC 09 Chadian 10 Central African 11 Nigerian 12 Malian 13 Chinese 14 Indian 15 Other countries This variable indicates the person's nationality. IPUMS Regional group <svar a="all" v="SD08A408 SD08A508">6. To what regional group does [the respondent] belong?<br /><div class="i1">[] 1 Northern Sudanese<br />[] 2 Southern Sudanese<br />[] 3 Non Sudanese<br />[] 4 No response</div><br /></svar> Sudan 2008: All persons 1 Northern Sudanese 2 Southern Sudanese 3 Non-Sudanese This variable indicates the person's regional group (Northern or Southern). IPUMS Region of origin <svar a="all" v="SD08A409 SD08A509">7. What is [the respondent's] region of origin?<br /><div class="i1">[] 1 Northern<br />[] 2 Eastern<br />[] 3 Khartoum<br />[] 4 Central<br />[] 5 Kordofan<br />[] 6 Darfur<br />[] 7 Upper Nile<br />[] 8 Bahr El Ghazal<br />[] 9 Equatoria<br />[] 10 Not Sudan<br />[] 11 No response</div><br /></svar> Sudan 2008: All persons 01 Northern 02 Eastern 03 Khartoum 04 Central 05 Kordofan 06 Darfur 07 Upper Nile 08 Bahr El Ghazal 09 Equatoria 10 Not Sudan 11 Unknown This variable indicates the person's region of origin. IPUMS State of birth <svar a="all" v="SD08A410 SD08A510">8. In what state was [the respondent] born?<br /><div class="i1">If not born in Sudan, code "99". Use the state codes on the separate sheet<br /><br />_ _</div><br /></svar> Sudan 2008: All persons 11 Northern 12 Nahr El Nil 21 Red Sea 22 Kassala 23 Al Gedarif 31 Khartoum 41 Al Gezira 42 White Nile 43 Sinnar 44 Blue Nile 51 North Kordofan 52 South Kordofan 61 North Darfur 62 West Darfur 63 South Darfur 71 Upper Nile 72 Jonglei 73 Unity 81 Warrap 82 Northern Bahr El Ghazal 83 Western Bahr El Ghazal 84 Lakes 91 Western Equatoria 92 Central Equatoria 93 Eastern Equatoria 99 Abroad This variable indicates the person's state of birth. IPUMS State of usual residence <svar a="all" v="SD08A411 SD08A412 SD08A511 SD08A512">9. What is [the respondent's] current usual state of usual residence? Where [the respondent] lived or intends to live for 6 months or more.<br /><div class="i1">If foreigner less than 1 year old, code "99". Use the state codes on the separate sheet.<br /><br />_ _</div><br /></svar> Sudan 2008: All persons 11 Northern 12 Nahr El Nil 21 Red Sea 22 Kassala 23 Al Gedarif 31 Khartoum 41 Al Gezira 42 White Nile 43 Sinnar 44 Blue Nile 51 North Kordofan 52 South Kordofan 61 North Darfur 62 West Darfur 63 South Darfur 71 Upper Nile 72 Jonglei 73 Unity 81 Warrap 82 Northern Bahr El Ghazal 83 Western Bahr El Ghazal 84 Lakes 91 Western Equatoria 92 Central Equatoria 93 Eastern Equatoria 99 Abroad This variable indicates the person's state of usual residence. IPUMS Duration of residence <svar a="all" v="SD08A413 SD08A513">10. How many years has [the respondent] lived continuously in the state of usual residence?<br /><div class="i1">If less than one year, code "0". If foreigner less than one year, code "99"<br /><br />_ _</div><br /></svar> Sudan 2008: All persons 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 years and beyond 99 Unknown This variable indicates the number of years the person has lived continuously in the state of usual residence. IPUMS Previous residence 1 year ago <svar a="all" v="SD08A414 SD08A514">11. In what state did [the respondent] usually reside this time last year?<br /><div class="i1">If foreigner less than 1 year, code "99". Use the state codes on the separate sheet.<br /><br />_ _</div><br /></svar> Sudan 2008: All persons 11 Northern 12 Nahr El Nil 21 Red Sea 22 Kassala 23 Al Gedarif 31 Khartoum 41 Al Gezira 42 White Nile 43 Sinnar 44 Blue Nile 51 North Kordofan 52 South Kordofan 61 North Darfur 62 West Darfur 63 South Darfur 71 Upper Nile 72 Jonglei 73 Unity 81 Warrap 82 Northern Bahr El Ghazal 83 Western Bahr El Ghazal 84 Lakes 91 Western Equatoria 92 Central Equatoria 93 Eastern Equatoria 98 Abroad This variable indicates the person's previous state of residence last year. IPUMS Mother's survival <svar a="all" v="SD08A415 SD08A515 SD08A566">12. Is [the respondent's] biological mother alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Don't know</div><br /></svar> Sudan 2008: All persons 1 Mother alive 2 Mother dead This variable indicates whether the person's mother is still alive. IPUMS Father's survival <svar a=" SD08A416 SD08A516" v="SD08A416 SD08A516 SD08A566">13. Is [the respondent's] biological father alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Don't know</div><br /></svar> Sudan 2008: All persons 1 Father alive 2 Father dead This variable indicates whether the person's father is still alive. IPUMS Limited use of leg(s) <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has limited use of leg(s). IPUMS Loss of leg(s) <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has loss of leg(s). IPUMS Limited use of arm(s) <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has limited use of arm(s). IPUMS Loss of arm(s) <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has loss of arm(s). IPUMS Difficulty in hearing <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has difficulty in hearing. IPUMS Deaf <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person is deaf. IPUMS Difficulty seeing <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has difficulty in seeing. IPUMS Blind <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person is blind. IPUMS Difficulty in speaking <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has difficulty in speaking. IPUMS Mute <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person is mute. IPUMS Mental difficulty <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 Yes 2 No This variable indicates whether the person has mental difficulty. IPUMS Have disability <svar a="all" v="SD08A417 SD08A418 SD08A419 SD08A420 SD08A421 SD08A422 SD08A423 SD08A424 SD08A425 SD08A426 SD08A427 SD08A428 SD08A429 SD08A517 SD08A518 SD08A519 SD08A520 SD08A521 SD08A522 SD08A523 SD08A524 SD08A525 SD08A526 SD08A527 SD08A528 SD08A529 SD08A567">14. Does [the respondent] have any difficulty in moving, seeing, hearing, speaking or learning?<br /><div class="i1">(Mark all that apply)<br /><br />[] 1 Limited use of legs<br />[] 2 Loss of leg(s)<br />[] 3 Limited use of arms<br />[] 4 Loss of arm(s)<br />[] 5 Difficulty in hearing<br />[] 6 Deaf<br />[] 7 Difficulty in seeing<br />[] 8 Blind<br />[] 9 Difficulty in speaking<br />[] 10 Mute<br />[] 11 Mental disability<br />[] 12 No disability<br />[] 13 Don't know</div><br /></svar> Sudan 2008: All persons 1 No disability 2 Have disability This variable indicates whether the person has no disability(ies). IPUMS Literacy <svar v="SD08A430 SD08A431 SD08A432 SD08A433 SD08A530 SD08A531 SD08A532 SD08A533"><span class="em">Education status</span><br />[Questions 15 - 18: Persons age 6 or older]<br /></svar></p> <p><svar a="all" v="SD08A430 SD08A530">15. Can [the respondent] read and write with understanding a simple sentence in any language?<br /><div class="i1">[] 1 Yes<br />[] 2 No</div><br /></svar> Sudan 2008: Persons age 6+ [discrepancies: none] 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the person is literate. IPUMS School attendence <svar v="SD08A430 SD08A431 SD08A432 SD08A433 SD08A530 SD08A531 SD08A532 SD08A533"><span class="em">Education status</span><br />[Questions 15 - 18: Persons age 6 or older]<br /></svar></p> <p><svar a="all" v="SD08A431 SD08A531">16. Has [the respondent] ever attended, or is currently attending school this year?<br /><div class="i1">[] 1 Currently attending<br />[] 2 Previously attended (skip to Q18)<br />[] 3 Never attended (skip to Q19)</div><br /></svar> Sudan 2008: Persons age 6+ [discrepancies: none] 1 Currently attending 2 Previously attended 3 Never attended 9 NIU (not in universe) This variable indicates whether the person has ever attended school. IPUMS School level attending <svar v="SD08A430 SD08A431 SD08A432 SD08A433 SD08A530 SD08A531 SD08A532 SD08A533"><span class="em">Education status</span><br />[Questions 15 - 18: Persons age 6 or older]<br /></svar></p> <p><svar a="all" v="SD08A432 SD08A532">17. For those currently attending: what is the grade and level that [the respondent] is attending?<br /><div class="i1">[Q17 is asked of persons age 6 or older who are currently attending school, as per Q16.]<br /><br />[] 1 P1<br />[] 2 P2<br />[] 3 P3<br />[] 4 P4<br />[] 5 P5<br />[] 6 P6<br />[] 7 P7<br />[] 8 P8<br />[] 9 S1<br />[] 10 S2<br />[] 11 S3<br />[] 12 S4<br />[] 13 S5<br />[] 14 S6<br />[] 15 Post secondary diploma program<br />[] 16 College<br />[] 17 University<br />[] 18 Master degree<br />[] 19 Ph.D. degree</div><br /></svar> Sudan 2008: Persons age 6+ who are currently attending school [discrepancies: type I 1.9%; type II none] 01 P1 02 P2 03 P3 04 P4 05 P5 06 P6 07 P7 08 P8 09 S1 10 S2 11 S3 12 S4 13 S5 14 S6 15 Post secondary/diploma program 16 College 17 University 18 Masters program 19 PhD program 98 Unknown 99 NIU (not in universe) This variable indicates the school level the person is attending. IPUMS Education attainment <svar v="SD08A430 SD08A431 SD08A432 SD08A433 SD08A530 SD08A531 SD08A532 SD08A533"><span class="em">Education status</span><br />[Questions 15 - 18: Persons age 6 or older]<br /></svar></p> <p><svar a="all" v="SD08A433 SD08A533">18. What is the highest level [the respondent] completed?<br /><div class="i1">[Q18 is asked of persons age 6 or older who are currently attending school or have attended school, as per Q16.]<br /><br />[] 1 No qualification (previously)<br />[] 2 Incomplete primary (currently)<br />[] 3 Primary 4<br />[] 4 Primary 6<br />[] 5 Primary 8<br />[] 6 Junior 3<br />[] 7 Junior 4<br />[] 8 Secondary 3<br />[] 9 Secondary 4<br />[] 10 Secondary 5<br />[] 11 Secondary 6<br />[] 12 Postsecondary diploma<br />[] 13 University first degree<br />[] 14 Postgraduate diploma<br />[] 15 Master's degree<br />[] 16 Ph.D. degree<br />[] 17 <span class="lang">Khawa</span></div><br /></svar> Sudan 2008: Persons who ever attended school [discrepancies: type I 0.1%; type II none] 01 No qualification 02 Incomplete primary 03 Primary 4 04 Primary 6 05 Primary 8 06 Junior 3 07 Junior 4 08 Secondary 3 09 Secondary 4 10 Secondary 5 11 Secondary 6 12 Post-secondary diploma 13 University first degree 14 Post-graduate diploma 15 Masters degree 16 PhD degree 17 Khalwa 98 Unknown 99 NIU (not in universe) This variable indicates the person's highest level of educational attainment. IPUMS Activity status <svar v="SD08A434 SD08A435 SD08A436 SD08A437 SD08A438 SD08A534 SD08A535 SD08A536 SD08A537 SD08A538"><span class="em">Economic activity</span><br />[Questions 19 - 23: Persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SD08A434 SD08A534">19. During the week before census night, did [the respondent] work at least one hour for pay (or without pay), profit, in kind, or for family business?<br /><div class="i1">[] 1 Worked (skip to Q21)<br />[] 2 Did not work but have a job to go back to (skip to Q21)<br />[] 3 Did not work but worked before and seeking work and available for work (skip to Q21)<br />[] 4 Did not work, seeking work for the first time and available for work (skip to Q24)<br />[] 5 Did not work and not seeking work</div><br /></svar> Sudan 2008: Persons age 10+ [discrepancies: none] 1 Worked last week 2 Temporarily away from job 3 Worked before and seeking work 4 First time job seeker 5 Not working or seeking work 9 NIU (not in universe) This variable indicates the person's employment status. IPUMS Reason for economic inactivity <svar v="SD08A434 SD08A435 SD08A436 SD08A437 SD08A438 SD08A534 SD08A535 SD08A536 SD08A537 SD08A538"><span class="em">Economic activity</span><br />[Questions 19 - 23: Persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SD08A435 SD08A535">20. For those who did no work and were not seeking work, why did [the respondent] not seek work?<br /><div class="i1">[Q20 is asked of persons age 10 or older who did not work and are not seeking work, as per Q19.]<br /><br />[] 1 No hope of finding job<br />[] 2 Full-time student<br />[] 3 Income recipient<br />[] 4 Too old<br />[] 5 Disabled / too sick<br />[] 6 Full-time homemaker / housewife<br />[] 7 Pensioner / retired</div><br /></svar> Sudan 2008: Persons age 10+ who did not work and were not seeking work last week [type I 5.2%; type II 35.7%] 1 No hope to find job 2 Full-time student 3 Income recipient 4 Too old 5 Disabled/too sick 6 Full-time homemaker 7 Pensioner/retired 8 Unknown 9 NIU (not in universe) This variable indicates the reason for economic inactivity. IPUMS Occupation <svar v="SD08A434 SD08A435 SD08A436 SD08A437 SD08A438 SD08A534 SD08A535 SD08A536 SD08A537 SD08A538"><span class="em">Economic activity</span><br />[Questions 19 - 23: Persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SD08A436 SD08A536">21. For those who worked or have worked before (Q19, codes 1-3), state in detail, the main job that [the respondent] was engaged in during the week before census night?<br /><div class="i1">[Q21 is asked of persons age 10 or older who worked, did not work but have a job to go back to, or did not work but last week but have work and seeking work and available for work, as per Q19.]<br /><br />Occupation ________</div><br /></svar> Sudan 2008: Persons age 10+ who worked, or were temporary away from job, or were seeking work not for the first time [type I 1%; type II 5.4%] 01 Commissioned armed forces officers 02 Non-commissioned armed forces officers 03 Armed forces occupations, other ranks 11 Chief executives senior officials and legislators 12 Administrative and commercial managers 13 Production and specialized services managers 14 Hospitality, retail and other services managers 21 Science and engineering professionals 22 Health professionals 23 Teaching professionals 24 Business and administration professionals 25 Information and communications technology (ICT) professionals 26 Legal, social and cultural professionals 31 Science and engineering associate professionals 32 Health associate professionals 33 Business and administration associate professionals 34 Legal, social, cultural and related associate professionals 35 Information and communications technicians (ICT) 41 General and keyboard clerks 42 Customer services clerks 43 Numerical and material recording clerks 44 Other clerical support workers 51 Personal service workers 52 Sales workers 54 Protective services workers 61 Market-oriented skilled agricultural workers 62 Market-oriented skilled forestry, fishery and hunting workers 63 Subsistence farmers, fishers, hunters and gatherers 71 Building and related trades workers, excluding electricians 72 Metal, machinery and related trades workers 73 Handicraft and printing workers 74 Electrical and electronic trades workers 75 Food processing, wood working, garment and other craft and related trades workers 81 Stationary plant and machine operators 83 Drivers and mobile plant operators 91 Cleaners and helpers 92 Agricultural, forestry and fishery labourers 93 Labourers in mining, construction, manufacturing and transport 94 Food preparation assistants 95 Street and related sales and service workers 96 Refuse workers and other elementary workers 90 Other occupation, response suppressed 98 Unknown 99 NIU (not in universe) This variable indicates the person's occupation. IPUMS Industry <svar v="SD08A434 SD08A435 SD08A436 SD08A437 SD08A438 SD08A534 SD08A535 SD08A536 SD08A537 SD08A538"><span class="em">Economic activity</span><br />[Questions 19 - 23: Persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SD08A437 SD08A537">22. For those who worked or have worked before (Q19, codes 1-3), what was [the respondent's] place of work or main activity of [the respondent's] place of work during the week before census night?<br /><div class="i1">[Q21 is asked of persons age 10 or older who worked, did not work but have a job to go back to, or did not work but last week but have work and seeking work and available for work, as per Q19.]<br /><br />Industry ________ _ _</div><br /></svar> Sudan 2008: Persons age 10+ who worked, or were temporary away from job, or were seeking work not for the first time [type I 5.5%; type II 2.4%] 001 Crop and animal production, hunting and related service activities 002 Forestry and logging 003 Fishing and aquaculture 006 Extraction of crude petroleum and natural gas 007 Mining of metal ores 008 Other mining and quarrying 010 Manufacture of food products 011 Manufacture of beverages 012 Manufacture of tobacco products 013 Manufacture of textiles 014 Manufacture of wearing apparel 015 Manufacture of leather and related products 016 Manufacture of wood and of products of wood and cork, except furniture 018 Printing and reproduction of recorded media 019 Manufacture of coke and refined petroleum products 020 Manufacture of chemicals and chemical products 021 Manufacture of pharmaceuticals, medicinal chemical and botanical products 022 Manufacture of rubber and plastics products 023 Manufacture of other non-metallic mineral products 024 Manufacture of basic metals 025 Manufacture of fabricated metal products, except machinery and equipment 029 Manufacture of motor vehicles, trailers and semi-trailers 031 Manufacture of furniture 032 Other manufacturing 033 Repair and installation of machinery and equipment 035 Electricity, gas, steam and air conditioning supply 036 Water collection, treatment and supply 037 Sewerage 038 Waste collection, treatment and disposal activities 041 Construction of buildings 042 Civil engineering 043 Specialized construction activities 045 Wholesale and retail trade and repair of motor vehicles and motorcycles 046 Wholesale trade, except of motor vehicles and motorcycles 047 Retail trade, except of motor vehicles and motorcycles 049 Land transport and transport via pipelines 050 Water transport 051 Air transport 052 Warehousing and support activities for transportation 053 Postal and courier activities 055 Accommodation 056 Food and beverage service activities 058 Publishing activities 059 Motion picture, video and television programme production, sound recording and music publishing activities 060 Programming and broadcasting activities 061 Telecommunications 062 Computer programming, consultancy and related activities 064 Financial service activities, except insurance and pension funding 065 Insurance, reinsurance and pension funding, except compulsory social security 066 Activities auxiliary to financial service and insurance activities 068 Real estate activities 069 Legal and accounting activities 071 Architectural and engineering activities 072 Scientific research and development 074 Other professional, scientific and technical activities 075 Veterinary activities 077 Rental and leasing activities 079 Travel agency, tour operator, reservation service and related activities 080 Security and investigation activities 081 Services to buildings and landscape activities 082 Office administrative, office support and other business support activities 084 Public administration and defence 085 Education 086 Human health activities 090 Creative, arts and entertainment activities 091 Libraries, archives, museums and other cultural activities 092 Gambling and betting activities 093 Sports activities and amusement and recreation activities 094 Activities of membership organizations 095 Repair of computers and personal and household goods 096 Other personal service activities 097 Activities of households as employers of domestic personnel 098 Undifferentiated goods- and services-producing activities of private households for own use 099 Activities of extraterritorial organizations and bodies 100 Other industry, response suppressed 998 Unknown 999 NIU (not in universe) This variable indicates the industry the person worked in. IPUMS Class of worker <svar v="SD08A434 SD08A435 SD08A436 SD08A437 SD08A438 SD08A534 SD08A535 SD08A536 SD08A537 SD08A538"><span class="em">Economic activity</span><br />[Questions 19 - 23: Persons age 10 or older]<br /></svar></p> <p><svar a="all" v="SD08A438 SD08A538">23. For those who worked or have worked before, what was [the respondent's] employment status?<br /><div class="i1">[Q21 is asked of persons age 10 or older who worked, did not work but have a job to go back to, or did not work but last week but have work and seeking work and available for work, as per Q19.]<br /><br />[] 1 Paid employee<br />[] 2 Employer<br />[] 3 Own account worker<br />[] 4 Unpaid family worker<br />[] 5 Unpaid working for others</div><br /></svar> Sudan 2008: Persons age 10+ who worked, or were temporary away from job, or were seeking work not for the first time [discrepancies: none] 1 Paid employee 2 Employer 3 Own account worker 4 Unpaid family worker 5 Unpaid working for others 9 NIU (not in universe) This variable indicates the person's class of worker. IPUMS Marital status <svar v="SD08A439 SD08A440 SD08A539 SD08A540"><span class="em">Marital status</span><br />[Questions 24 - 25: Persons age 12 or older]<br /></svar></p> <p><svar a="all" v="SD08A439 SD08A539">24. What is [the respondent's] marital status?<br /><div class="i1">[] 1 Never married<br />[] 2 Married<br />[] 3 Widowed<br />[] 4 Divorced</div><br /></svar> Sudan 2008: Persons age 12+ [discrepancies: none] 1 Never married 2 Married 3 Widowed 4 Divorced 9 NIU (not in universe) This variable indicates the person's marital status. IPUMS Age at first marriage <svar v="SD08A439 SD08A440 SD08A539 SD08A540"><span class="em">Marital status</span><br />[Questions 24 - 25: Persons age 12 or older]<br /></svar></p> <p><svar a="all" v="SD08A440 SD08A540">25. For all ever-married persons: what was [the respondent's] age at first marriage?<br /><div class="i1">Code age in completed years<br />_ _</div><br /></svar> Sudan 2008: Ever-married persons age 12+ [discrepancies: type I none; type II 3%] 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 98 Unknown 99 NIU (not in universe) This variable indicates the person's age, in completed years, at first marriage. IPUMS Males ever born <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A441 SD08A442 SD08A541 SD08A542 SD08A559 SD08A560">26. What is the total number of children [the respondent] has ever born alive? (even if the child was only alive for a short time and died soon after birth)<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16+ 99 NIU (not in universe) This variable indicates the number of male children ever born to the person. IPUMS Females ever born <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A441 SD08A442 SD08A541 SD08A542 SD08A559 SD08A560">26. What is the total number of children [the respondent] has ever born alive? (even if the child was only alive for a short time and died soon after birth)<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14+ 99 NIU (not in universe) This variable indicates the number of female children ever born to the person. IPUMS Male children at home <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A443 SD08A444 SD08A543 SD08A544 SD08A556 SD08A561 SD08A562 SD08A563">27. How many of these children are living with [the respondent] in this household?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12+ 99 NIU (not in universe) This variable indicates the number of male children ever born to the person that are living with the person in the household. IPUMS Female children at home <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A443 SD08A444 SD08A543 SD08A544 SD08A556 SD08A561 SD08A562 SD08A563">27. How many of these children are living with [the respondent] in this household?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) This variable indicates the number of female children ever born to the person that are living with the person in the household. IPUMS Male children living elsewhere <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a=" SD08A445 SD08A446 SD08A545 SD08A546 SD08A557" v="SD08A445 SD08A446 SD08A545 SD08A546 SD08A557 SD08A556 SD08A561 SD08A562 SD08A563">28. How many of those children are living elsewhere (not in this household)?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) This variable indicates the number of male children ever born to the person that are living elsewhere. IPUMS Female children living elsewhere <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a=" SD08A445 SD08A446 SD08A545 SD08A546 SD08A557" v="SD08A445 SD08A446 SD08A545 SD08A546 SD08A557 SD08A556 SD08A561 SD08A562 SD08A563">28. How many of those children are living elsewhere (not in this household)?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) This variable indicates the number of female children ever born to the person that are living elsewhere. IPUMS Male children deceased <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A447 SD08A448 SD08A547 SD08A548 SD08A558">29. How many of those children are no longer alive?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) This variable indicates the number of male children ever born to the person that are deceased. IPUMS Female children deceased <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A447 SD08A448 SD08A547 SD08A548 SD08A558">29. How many of those children are no longer alive?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10+ 99 NIU (not in universe) This variable indicates the number of female children ever born to the person that are deceased. IPUMS Any births last 12 months <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A449 SD08A549">30. Did [the respondent] give birth during the last 12 months?<br /><div class="i1">If no birth in last 12 months, go to question 33.<br /><br />Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: type I none; type II 1.5%] 1 Yes 2 No 8 Unknown 9 NIU (not in universe) This variable indicates whether the person had any births in the last 12 months. IPUMS Males born last 12 months <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A450 SD08A451 SD08A550 SD08A551 SD08A564">31. How many children has [the respondent] given birth to in the last 12 months?<br /><div class="i1">[Q31 was asked of females who have given birth during the last 12 months, as per Q30.]<br /><br />Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: type I none; type II 1.8%] 1 1 2 2 8 Unknown 9 NIU (not in universe) This variable indicates the number of male children born in the last 12 months. IPUMS Females born last 12 months <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A450 SD08A451 SD08A550 SD08A551 SD08A564">31. How many children has [the respondent] given birth to in the last 12 months?<br /><div class="i1">[Q31 was asked of females who have given birth during the last 12 months, as per Q30.]<br /><br />Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: type I none; type II 1.8%] 1 1 2 2 8 Unknown 9 NIU (not in universe) This variable indicates the number of female children born in the last 12 months. IPUMS Males born last 12 months surviving <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A452 SD08A453 SD08A552 SD08A553 SD08A565">32. How many of these children born in the last 12 months are still alive?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: type I none; type II 1.8%] 1 1 2 2 8 Unknown 9 NIU (not in universe) This variable indicates the number of male children born in the last 12 months who are still alive. IPUMS Females born last 12 months surviving <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A452 SD08A453 SD08A552 SD08A553 SD08A565">32. How many of these children born in the last 12 months are still alive?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: type I none; type II 1.8%] 1 1 2 2 8 Unknown 9 NIU (not in universe) This variable indicates the number of female children born in the last 12 months who are still alive. IPUMS Flag: Age Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Nationality Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Regional group Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Region of origin Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: State of birth Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: State of usual residence Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Duration of residence Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: State of previous residence Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Mother's survival Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Father's survival Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Loss of leg(s) Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank Flag: Loss of leg(s). IPUMS Flag: Loss of arm(s) Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Deaf Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Blind Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Mute Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Literacy Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: School attendence Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: School level currently attending Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Education attainment Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Activity status Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Reason for economic inactivity Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Occupation Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Economic sector Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Employment status Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Marital status Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank Flag: Marital status. IPUMS Flag: Age at first marriage Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Males ever born Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Females ever born Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Male children at home Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Female children at home Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Male children living elsewhere Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Female children living elsewhere Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Male children deceased Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Female children deceased Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Any births last 12 months Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Males born last 12 months Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Females born last 12 months Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Males born last 12 months (alive) Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Flag: Females born last 12 months (alive) Sudan 2008: All persons No imputation 1 Logical from blank 2 Logical from valid non-blank 3 Logical from invalid non-blank 4 Imputation from blank 5 Imputation from valid non-blank 6 Imputation from invalid non-blank This variable means that the indicated variable was edited during processing. IPUMS Person weight Sudan 2008: All persons This variable indicates the person weight. This is a 6-digit numeric variable with 4 implied decimal places IPUMS Children living in household <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A443 SD08A444 SD08A543 SD08A544 SD08A556 SD08A561 SD08A562 SD08A563">27. How many of these children are living with [the respondent] in this household?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15+ 99 NIU (not in universe) This variable indicates the number of own children living in the household. IPUMS Children living elsewhere <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a=" SD08A445 SD08A446 SD08A545 SD08A546 SD08A557" v="SD08A445 SD08A446 SD08A545 SD08A546 SD08A557 SD08A556 SD08A561 SD08A562 SD08A563">28. How many of those children are living elsewhere (not in this household)?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13+ 99 NIU (not in universe) This variable indicates the number of own children living elsewhere. IPUMS Children who have died <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A447 SD08A448 SD08A547 SD08A548 SD08A558">29. How many of those children are no longer alive?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12+ 99 NIU (not in universe) This variable indicates the number of children who have died. IPUMS Children ever born <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A441 SD08A442 SD08A541 SD08A542 SD08A559 SD08A560">26. What is the total number of children [the respondent] has ever born alive? (even if the child was only alive for a short time and died soon after birth)<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 99 NIU (not in universe) This variable indicates the number of children ever born to the person. IPUMS Children surviving <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A443 SD08A444 SD08A543 SD08A544 SD08A556 SD08A561 SD08A562 SD08A563">27. How many of these children are living with [the respondent] in this household?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar></p> <p><svar a=" SD08A445 SD08A446 SD08A545 SD08A546 SD08A557" v="SD08A445 SD08A446 SD08A545 SD08A546 SD08A557 SD08A556 SD08A561 SD08A562 SD08A563">28. How many of those children are living elsewhere (not in this household)?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18+ 99 NIU (not in universe) This variable indicates the number of own children who are still surviving. IPUMS Male children surviving <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A443 SD08A444 SD08A543 SD08A544 SD08A556 SD08A561 SD08A562 SD08A563">27. How many of these children are living with [the respondent] in this household?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar></p> <p><svar a=" SD08A445 SD08A446 SD08A545 SD08A546 SD08A557" v="SD08A445 SD08A446 SD08A545 SD08A546 SD08A557 SD08A556 SD08A561 SD08A562 SD08A563">28. How many of those children are living elsewhere (not in this household)?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13 14 14+ 99 NIU (not in universe) This variable indicates the number of male children ever born to the person who are still alive. IPUMS Female children surviving <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A443 SD08A444 SD08A543 SD08A544 SD08A556 SD08A561 SD08A562 SD08A563">27. How many of these children are living with [the respondent] in this household?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar></p> <p><svar a=" SD08A445 SD08A446 SD08A545 SD08A546 SD08A557" v="SD08A445 SD08A446 SD08A545 SD08A546 SD08A557 SD08A556 SD08A561 SD08A562 SD08A563">28. How many of those children are living elsewhere (not in this household)?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: none] 00 01 1 02 2 03 3 04 4 05 5 06 6 07 7 08 8 09 9 10 10 11 11 12 12 13 13+ 99 NIU (not in universe) This variable indicates the number of female children ever born to the person who are still alive. IPUMS Children born last year <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A450 SD08A451 SD08A550 SD08A551 SD08A564">31. How many children has [the respondent] given birth to in the last 12 months?<br /><div class="i1">[Q31 was asked of females who have given birth during the last 12 months, as per Q30.]<br /><br />Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: type I none; type II 1.8%] 1 1 2 2 3 3 4 4 8 Unknown 9 NIU (not in universe) This variable indicates the number of children born to the person last year. IPUMS Children born last year surviving <svar v="SD08A441 SD08A442 SD08A443 SD08A444 SD08A445 SD08A446 SD08A447 SD08A448 SD08A449 SD08A450 SD08A451 SD08A452 SD08A453 SD08A541 SD08A542 SD08A543 SD08A544 SD08A545 SD08A546 SD08A547 SD08A548 SD08A549 SD08A550 SD08A551 SD08A552 SD08A553 SD08A556 SD08A557 SD08A558 SD08A559 SD08A560 SD08A561 SD08A561 SD08A562 SD08A563 SD08A564 SD08A565"><span class="em">Number of children ever born alive</span><br />[Questions 26 - 32: Women aged 12 to 54 years (if in North Sudan only complete this section for women who are or have ever been married)]<br />If no children, write "00"<br /></svar></p> <p><svar a="all" v="SD08A452 SD08A453 SD08A552 SD08A553 SD08A565">32. How many of these children born in the last 12 months are still alive?<br /><div class="i1">Male _ _<br />Female _ _</div><br /></svar> Sudan 2008: Ever-married females age 12 to 54 [discrepancies: type I none; type II 1.8%] 1 1 2 2 3 3 4 4+ 8 Unknown 9 NIU (not in universe) This variable indicates the number of children born to the person last year who are still surviving. IPUMS Parents mortality status <svar a="all" v="SD08A415 SD08A515 SD08A566">12. Is [the respondent's] biological mother alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Don't know</div><br /></svar></p> <p><svar a=" SD08A416 SD08A516" v="SD08A416 SD08A516 SD08A566">13. Is [the respondent's] biological father alive?<br /><div class="i1">[] 1 Yes<br />[] 2 No<br />[] 3 Don't know</div><br /></svar> Sudan 2008: All persons 1 Father alive, mother alive 2 Father alive, mother dead 3 Father dead, mother alive 4 Father dead, mother dead This variable indicates the parent's mortality status. IPUMS