10 datasets found
  1. Historic US Census - 1900

    • redivis.com
    application/jsonl +7
    Updated Jan 10, 2020
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    Stanford Center for Population Health Sciences (2020). Historic US Census - 1900 [Dataset]. http://doi.org/10.57761/mez6-j880
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    avro, arrow, sas, stata, spss, csv, application/jsonl, parquetAvailable download formats
    Dataset updated
    Jan 10, 2020
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Feb 1, 1900 - Dec 31, 1900
    Area covered
    United States
    Description

    Documentation

    The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

    Historic data are scarce and often only exists in aggregate tables. The key advantage of the IPUMS data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

    In sum: the IPUMS data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

    The IPUMS 1900 census data was collected in June 1900. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

    Section 2

    This dataset was created on 2020-01-10 22:51:40.810 by merging multiple datasets together. The source datasets for this version were:

    IPUMS 1900 households: This dataset includes all households from the 1900 US census.

    IPUMS 1900 persons: This dataset includes all individuals from the 1910 US census.

    IPUMS 1900 Lookup: This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1900 datasets.

    Section 3

    The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

    Historic data are scarce and often only exists in aggregate tables. The key advantage of the IPUMS data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

    In sum: the IPUMS data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

    The IPUMS 1900 census data was collected in June 1900. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

  2. c

    United States Census Data, 1900: Public Use Sample

    • archive.ciser.cornell.edu
    • icpsr.umich.edu
    Updated Jan 20, 2020
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    Robert Higgs; Samuel Preston (2020). United States Census Data, 1900: Public Use Sample [Dataset]. http://doi.org/10.6077/j5/bkpbxo
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    Dataset updated
    Jan 20, 2020
    Authors
    Robert Higgs; Samuel Preston
    Area covered
    United States
    Variables measured
    Household, Individual
    Description

    This study was conducted under the auspices of the Center for Studies in Demography and Ecology at the University of Washington. It is a nationally representative sample of the population of the United States in 1900, drawn from the manuscript returns of individuals enumerated in the 1900 United States Census. Household variables include region, state and county of household, size of household, and type and ownership of dwelling. Individual variables for each household member include relationship to head of household, race, sex, age, marital status, number of children, and birthplace. Immigration variables include parents' birthplace, year of immigration and number of years in the United States. Occupation variables include occupation, coded by both the 1900 and 1950 systems, and number of months unemployed. Education variables include number of months in school, whether respondents could read or write a language, and whether they spoke English. (Source: downloaded from ICPSR 7/13/10)

    Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR07825.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

  3. n

    Early Indicators of Later Work Levels Disease and Death (EI) - Union Army...

    • neuinfo.org
    • rrid.site
    • +2more
    Updated Jan 29, 2022
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    (2022). Early Indicators of Later Work Levels Disease and Death (EI) - Union Army Samples Public Health and Ecological Datasets [Dataset]. http://identifiers.org/RRID:SCR_008921
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    Dataset updated
    Jan 29, 2022
    Description

    A dataset to advance the study of life-cycle interactions of biomedical and socioeconomic factors in the aging process. The EI project has assembled a variety of large datasets covering the life histories of approximately 39,616 white male volunteers (drawn from a random sample of 331 companies) who served in the Union Army (UA), and of about 6,000 African-American veterans from 51 randomly selected United States Colored Troops companies (USCT). Their military records were linked to pension and medical records that detailed the soldiers������?? health status and socioeconomic and family characteristics. Each soldier was searched for in the US decennial census for the years in which they were most likely to be found alive (1850, 1860, 1880, 1900, 1910). In addition, a sample consisting of 70,000 men examined for service in the Union Army between September 1864 and April 1865 has been assembled and linked only to census records. These records will be useful for life-cycle comparisons of those accepted and rejected for service. Military Data: The military service and wartime medical histories of the UA and USCT men were collected from the Union Army and United States Colored Troops military service records, carded medical records, and other wartime documents. Pension Data: Wherever possible, the UA and USCT samples have been linked to pension records, including surgeon''''s certificates. About 70% of men in the Union Army sample have a pension. These records provide the bulk of the socioeconomic and demographic information on these men from the late 1800s through the early 1900s, including family structure and employment information. In addition, the surgeon''''s certificates provide rich medical histories, with an average of 5 examinations per linked recruit for the UA, and about 2.5 exams per USCT recruit. Census Data: Both early and late-age familial and socioeconomic information is collected from the manuscript schedules of the federal censuses of 1850, 1860, 1870 (incomplete), 1880, 1900, and 1910. Data Availability: All of the datasets (Military Union Army; linked Census; Surgeon''''s Certificates; Examination Records, and supporting ecological and environmental variables) are publicly available from ICPSR. In addition, copies on CD-ROM may be obtained from the CPE, which also maintains an interactive Internet Data Archive and Documentation Library, which can be accessed on the Project Website. * Dates of Study: 1850-1910 * Study Features: Longitudinal, Minority Oversamples * Sample Size: ** Union Army: 35,747 ** Colored Troops: 6,187 ** Examination Sample: 70,800 ICPSR Link: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06836

  4. NCHS - Death rates and life expectancy at birth

    • healthdata.gov
    • data.virginia.gov
    • +6more
    application/rdfxml +5
    Updated Feb 25, 2021
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    data.cdc.gov (2021). NCHS - Death rates and life expectancy at birth [Dataset]. https://healthdata.gov/w/4r8i-dqgb/default?cur=Mlqc0NLzFD8
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    csv, json, application/rdfxml, application/rssxml, xml, tsvAvailable download formats
    Dataset updated
    Feb 25, 2021
    Dataset provided by
    data.cdc.gov
    Description

    This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex.

    Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below).

    Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm.

    SOURCES

    CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov).

    REFERENCES

    1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm.

    2. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

    3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf.

    4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf.

    5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

  5. NCHS - Childhood Mortality Rates

    • data.virginia.gov
    • healthdata.gov
    • +5more
    csv, json, rdf, xsl
    Updated Apr 1, 2022
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    Centers for Disease Control and Prevention (2022). NCHS - Childhood Mortality Rates [Dataset]. https://data.virginia.gov/dataset/nchs-childhood-mortality-rates
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    csv, json, rdf, xslAvailable download formats
    Dataset updated
    Apr 1, 2022
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This dataset of U.S. mortality trends since 1900 highlights childhood mortality rates by age group for age at death.

    Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below).

    Age groups for childhood death rates are based on age at death.

    SOURCES

    CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov).

    REFERENCES

    1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm.

    2. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

    3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf.

    4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf.

    5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

  6. NCHS - Age-adjusted Death Rates for Selected Major Causes of Death

    • data.virginia.gov
    • healthdata.gov
    • +5more
    csv, json, rdf, xsl
    Updated Mar 30, 2022
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    Centers for Disease Control and Prevention (2022). NCHS - Age-adjusted Death Rates for Selected Major Causes of Death [Dataset]. https://data.virginia.gov/dataset/nchs-age-adjusted-death-rates-for-selected-major-causes-of-death
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    rdf, json, csv, xslAvailable download formats
    Dataset updated
    Mar 30, 2022
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    This dataset of U.S. mortality trends since 1900 highlights trends in age-adjusted death rates for five selected major causes of death.

    Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below).

    Revisions to the International Classification of Diseases (ICD) over time may result in discontinuities in cause-of-death trends.

    SOURCES

    CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov).

    REFERENCES

    1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm.

    2. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

    3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf.

    4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf.

    5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

  7. c

    Great Britain Historical Database : Labour Markets Database, Government...

    • datacatalogue.cessda.eu
    • beta.ukdataservice.ac.uk
    Updated Nov 28, 2024
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    Gregory, I., University of London, Queen Mary and Westfield College; Gilbert, D. R., University of London, Queen Mary and Westfield College; Southall, H. R., University of London, Queen Mary and Westfield College (2024). Great Britain Historical Database : Labour Markets Database, Government Unemployment Statistics, 1901-1939 [Dataset]. http://doi.org/10.5255/UKDA-SN-3711-1
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    Dataset updated
    Nov 28, 2024
    Dataset provided by
    Department of Geography
    Authors
    Gregory, I., University of London, Queen Mary and Westfield College; Gilbert, D. R., University of London, Queen Mary and Westfield College; Southall, H. R., University of London, Queen Mary and Westfield College
    Time period covered
    Jan 1, 1977 - Jan 1, 1996
    Area covered
    United Kingdom
    Variables measured
    Cross-national, National, Unemployment statistics, Administrative units (geographical/political)
    Measurement technique
    Transcription, Compilation/Synthesis
    Description

    Abstract copyright UK Data Service and data collection copyright owner.

    The Great Britain Historical Database has been assembled as part of the ongoing Great Britain Historical GIS Project. The project aims to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain at sub-county scales. Further information about the project is available on A Vision of Britain webpages, where users can browse the database's documentation system online.

    The Great Britain Historical GIS Project has also produced digitised boundary data, which can be obtained from the UK Data Service Census Support service. Further information is available at census.ukdataservice.ac.uk


    Main Topics:

    The Great Britain Historical Database is a large database of British nineteenth and twentieth-century statistics. Where practical the referencing of spatial units has been integrated, data for different dates have been assembled into single tables.

    The Great Britain Historical Database currently contains :

    • Statistics from the 1861 Census and the Registrar General's reports, 1851-1861
    • Employment statistics from the census, 1841-1931
    • Demographic statistics from the census, 1841-1931
    • Mortality statistics from the Registrar General's reports, 1861-1920
    • Marriage statistics from the Registrar General's reports, 1841-1870
    • Trade union statistics for the Amalgamated Society of Engineers (ASE), 1851-1918
    • Trade union statistics for the Amalgamated Society of Carpenters and Joiners (ASCJ), 1863-1912
    • Official poor law statistics, 1859-1915 and 1919-1939
    • Wage statistics, 1845-1906
    • Hours of work statistics, 1900-1913
    • Small debt statistics from county courts, 1847-1913 and 1938

    There are six tables in this part of the Great Britain Historical Database :

    Tu_pc holds monthly local unemployment statistics for engineers (January 1902-December 1914), shipbuilders (January 1902-December 1914), printers (February 1902-December 1914) and carpenters and joiners (May 1901-October 1905). For details of the districts used please see the documentation.

    Div23_38 holds annual data taken from the official tabulations of the Ministry of Labour's Local Unemployment Index from 1923 to 1938 for eight divisions.

    Lui holds quarterly data taken from the official tabulations of the Ministry of Labour's Local Unemployment Index from January 1927 to July 1939.

    Lui_gaz provides locational information for the exchange areas listed in lui.

    Un_1928 holds information on registered unemployment at labour exchanges for 30th January 1928.

    Un_1933 holds information on registered unemployment at labour exchanges for 23rd January 1933.

    Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

  8. Comparative Socio-Economic, Public Policy, and Political Data,1900-1960

    • icpsr.umich.edu
    ascii, sas, spss
    Updated Jan 12, 2006
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    Hofferbert, Richard I. (2006). Comparative Socio-Economic, Public Policy, and Political Data,1900-1960 [Dataset]. http://doi.org/10.3886/ICPSR00034.v1
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    spss, sas, asciiAvailable download formats
    Dataset updated
    Jan 12, 2006
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Hofferbert, Richard I.
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/34/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/34/terms

    Area covered
    Canada, France, Mexico, Europe, Switzerland, Germany
    Description

    This study contains selected demographic, social, economic, public policy, and political comparative data for Switzerland, Canada, France, and Mexico for the decades of 1900-1960. Each dataset presents comparable data at the province or district level for each decade in the period. Various derived measures, such as percentages, ratios, and indices, constitute the bulk of these datasets. Data for Switzerland contain information for all cantons for each decennial year from 1900 to 1960. Variables describe population characteristics, such as the age of men and women, county and commune of origin, ratio of foreigners to Swiss, percentage of the population from other countries such as Germany, Austria and Lichtenstein, Italy, and France, the percentage of the population that were Protestants, Catholics, and Jews, births, deaths, infant mortality rates, persons per household, population density, the percentage of urban and agricultural population, marital status, marriages, divorces, professions, factory workers, and primary, secondary, and university students. Economic variables provide information on the number of corporations, factory workers, economic status, cultivated land, taxation and tax revenues, canton revenues and expenditures, federal subsidies, bankruptcies, bank account deposits, and taxable assets. Additional variables provide political information, such as national referenda returns, party votes cast in National Council elections, and seats in the cantonal legislature held by political groups such as the Peasants, Socialists, Democrats, Catholics, Radicals, and others. Data for Canada provide information for all provinces for the decades 1900-1960 on population characteristics, such as national origin, the net internal migration per 1,000 of native population, population density per square mile, the percentage of owner-occupied dwellings, the percentage of urban population, the percentage of change in population from preceding censuses, the percentage of illiterate population aged 5 years and older, and the median years of schooling. Economic variables provide information on per capita personal income, total provincial revenue and expenditure per capita, the percentage of the labor force employed in manufacturing and in agriculture, the average number of employees per manufacturing establishment, assessed value of real property per capita, the average number of acres per farm, highway and rural road mileage, transportation and communication, the number of telephones per 100 population, and the number of motor vehicles registered per 1,000 population. Additional variables on elections and votes are supplied as well. Data for France provide information for all departements for all legislative elections since 1936, the two presidential elections of 1965 and 1969, and several referenda held in the period since 1958. Social and economic data are provided for the years 1946, 1954, and 1962, while various policy data are presented for the period 1959-1962. Variables provide information on population characteristics, such as the percentages of population by age group, foreign-born, bachelors aged 20 to 59, divorced men aged 25 and older, elementary school students in private schools, elementary school students per million population from 1966 to 1967, the number of persons in household in 1962, infant mortality rates per million births, and the number of priests per 10,000 population in 1946. Economic variables focus on the Gross National Product (GNP), the revenue per capita per household, personal income per capita, income tax, the percentage of active population in industry, construction and public works, transportation, hotels, public administration, and other jobs, the percentage of skilled and unskilled industrial workers, the number of doctors per 10,000 population, the number of agricultural cooperatives in 1946, the average hectares per farm, the percentage of farms cultivated by the owner, tenants, and sharecroppers, the number of workhorses, cows, and oxen per 100 hectares of farmland in 1946, and the percentages of automobiles per 1,000 population, radios per 100 homes, and cinema seats per 1,000 population. Data are also provided on the percentage of Communists (PCF), Socialists, Radical Socialists, Conservatives, Gaullists, Moderates, Poujadists, Independents, Turnouts, and other political groups and p

  9. NCHS - Top Five Leading Causes of Death: United States, 1990, 1950, 2000

    • catalog.data.gov
    • healthdata.gov
    • +6more
    Updated Apr 21, 2022
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    Centers for Disease Control and Prevention (2022). NCHS - Top Five Leading Causes of Death: United States, 1990, 1950, 2000 [Dataset]. https://catalog.data.gov/dataset/nchs-top-five-leading-causes-of-death-united-states-1990-1950-2000
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    Dataset updated
    Apr 21, 2022
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Area covered
    United States
    Description

    This dataset contains information on the number of deaths and age-adjusted death rates for the five leading causes of death in 1900, 1950, and 2000. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

  10. d

    Great Britain Historical Database : Labour Markets Database, Poor Law...

    • b2find.dkrz.de
    Updated Oct 22, 2023
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    (2023). Great Britain Historical Database : Labour Markets Database, Poor Law Statistics, 1859-1939 - Dataset - B2FIND [Dataset]. https://b2find.dkrz.de/dataset/371f5516-5f9c-5c6b-be4d-86ca028691be
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    Dataset updated
    Oct 22, 2023
    Area covered
    Great Britain, United Kingdom
    Description

    Main Topics: The Great Britain Historical Database is a large database of British nineteenth and twentieth-century statistics. Where practical the referencing of spatial units has been integrated, data for different dates have been assembled into single tables. The Great Britain Historical Database currently contains :Statistics from the 1861 Census and the Registrar General's reports, 1851-1861 Employment statistics from the census, 1841-1931 Demographic statistics from the census, 1841-1931 Mortality statistics from the Registrar General's reports, 1861-1920 Marriage statistics from the Registrar General's reports, 1841-1870 Trade union statistics for the Amalgamated Society of Engineers (ASE), 1851-1918 Trade union statistics for the Amalgamated Society of Carpenters and Joiners (ASCJ), 1863-1912 Official poor law statistics, 1859-1915 and 1919-1939 Wage statistics, 1845-1906 Hours of work statistics, 1900-1913 Small debt statistics from county courts, 1847-1913 and 1938 There are eight tables in this part of the Great Britain Historical Database : Plaw_c holds county-level data for England and Wales on numbers of paupers taken from the Annual Reports of the Poor Law Board and later the Local Government Board for 1st January and 1st July from January 1859 to January 1915, plus January 1919. Plaw_c_f holds a full transcript of county-level pauperage statistics for England and Wales taken from the Annual Reports of the Poor Law Board and later the Local Government Board for 1st January and 1st July 1860, 1863, 1866, 1868 and 1879. Plaw_u holds data taken from the Returns to Parliament made by the Poor Law Board, and later the Local Government Board listing number of paupers in each poor law union on the 1st January and 1st July. Coverage is as follows: all poor law unions in Lancashire for 1st January and 1st July from 1860 to 1871; all poor law unions in England and Wales for 1st January only from 1900 to 1912; all unions in London, Lancashire, Durham and selected major urban unions for 1st January and 1st July in 1875, 1879 and 1880. Plaw_u_f contains a full transcript of poor law union-level pauperage statistics for selected unions taken from the Returns to Parliament. Coverage is as follows: all poor law unions in Lancashire for 1st January and 1st July from 1860 to 1871; all unions in Suffolk, Norfolk, Cambridgeshire, Lincolnshire, Nottinghamshire, Derbyshire, Cheshire and the East and West Ridings of Yorkshire for 1st January and 1st July in 1860, 1863, 1866, 1868 and 1869. Plaw_iw holds inter-war poor law statistics taken from the Returns to Parliament for 1st January only for all poor law unions in England and Wales from 1922 to 1930, and for all counties and county-boroughs in England and Wales from 1931 to 1939. Plaw_20 holds poor law statistics for England and Wales for 1920 and 1921 for selected poor law union for 1st January only. Plu_gaz converts names of poor law unions as they appear in plaw_u, plaw_u_f, plaw_iw and plaw_20 into the form used in the GIS. Plu_gis holds names and counties of poor law unions as they appear in the GIS; used for checking names and constructing plu_gaz. Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

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Stanford Center for Population Health Sciences (2020). Historic US Census - 1900 [Dataset]. http://doi.org/10.57761/mez6-j880
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Historic US Census - 1900

Explore at:
avro, arrow, sas, stata, spss, csv, application/jsonl, parquetAvailable download formats
Dataset updated
Jan 10, 2020
Dataset provided by
Redivis Inc.
Authors
Stanford Center for Population Health Sciences
Time period covered
Feb 1, 1900 - Dec 31, 1900
Area covered
United States
Description

Documentation

The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

Historic data are scarce and often only exists in aggregate tables. The key advantage of the IPUMS data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

In sum: the IPUMS data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

The IPUMS 1900 census data was collected in June 1900. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

Section 2

This dataset was created on 2020-01-10 22:51:40.810 by merging multiple datasets together. The source datasets for this version were:

IPUMS 1900 households: This dataset includes all households from the 1900 US census.

IPUMS 1900 persons: This dataset includes all individuals from the 1910 US census.

IPUMS 1900 Lookup: This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1900 datasets.

Section 3

The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

Historic data are scarce and often only exists in aggregate tables. The key advantage of the IPUMS data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

In sum: the IPUMS data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

The IPUMS 1900 census data was collected in June 1900. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

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