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The population rate of change of Columbia Metro Area (SC) was 1.03% in 2018.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

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Demographics and Population Datasets Involving Columbia Metro Area (SC)

  • API

    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2013-02-08T20:03:40.000Z

    basic characteristics of people and housing for individual 2010 census block groups

  • API

    Labor Force Demographic Characteristics by Commuting Mode Split: 2012 - 2016

    data.cambridgema.gov | Last Updated 2019-09-17T17:16:51.000Z

    This data set provides demographic and journey to work characteristics of the Cambridge Labor Force by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time leaving home, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Labor Force consist of all persons who live in Cambridge who work or are actively seeking employment. For more information on Journey to Work data in Cambridge, please see the full 2015 report (https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).

  • API

    1980 Census Detailed Census Tract Data

    data.kcmo.org | Last Updated 2013-02-08T20:55:45.000Z

    detailed 1980 characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    Social Vulnerability Index for Virginia by Census Tract, 2018

    data.virginia.gov | Last Updated 2021-02-22T20:18:07.000Z

    "ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI or simply SVI, hereafter) to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking." For more see https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html

  • API

    2010 Census/ACS Basic Census Tract Data

    data.kcmo.org | Last Updated 2014-06-10T19:42:31.000Z

    basic characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    Rate of Hospitalizations for Opioid Overdose per 100,000 Residents by Demographics CY 2016- 2017 Statewide Health Care Cost Containment Council (PHC4)

    data.pa.gov | Last Updated 2019-01-18T20:03:25.000Z

    Rate of hospitalization for opioid overdose per 100,000 PA Residents categorized by principal diagnosis of heroin or opioid pain medication overdose by year and demographic. This analysis is restricted to Pennsylvania residents age 15 and older who were hospitalized in Pennsylvania general acute care hospitals. Disclaimer: PHC4’s database contains statewide hospital discharge data submitted to PHC4 by Pennsylvania hospitals. Every reasonable effort has been made to ensure the accuracy of the information obtained from the Uniform Claims and Billing Form (UB-82/92/04) data elements. Computer collection edits and validation edits provide opportunity to correct specific errors that may have occurred prior to, during or after submission of data. The ultimate responsibility for data accuracy lies with individual providers. PHC4 agents and staff make no representation, guarantee, or warranty, expressed or implied that the data received from the hospitals are error-free, or that the use of this data will prevent differences of opinion or disputes with those who use published reports or purchased data. PHC4 will bear no responsibility or liability for the results or consequences of its use.

  • API

    2010 Census/ACS Basic Census Tract Data

    data.kcmo.org | Last Updated 2019-04-19T19:05:00.000Z

    basic characteristics of people and housing for individual 2010 census tract portions inside or outside KCMO

  • API

    LA County VMT by City (2016) (Modelled)

    data.lacounty.gov | Last Updated 2019-12-06T23:13:12.000Z

    Emissions from passenger vehicles and trucks are estimated based on VMT by vehicle type. VMT for each jurisdiction is estimated using trip-based travel forecasting models developed by Southern California Association of Governments (SCAG). SCAG’s regional travel demand model analyzes transportation network and socioeconomic data such as population, household, and employment, to forecast daily vehicle trips for each traffic analysis zone (TAZ). Model outputs include: • Vehicle trips by type: including cars, light trucks, medium duty trucks, heavy duty trucks, and transit vehicles • Vehicle trip lengths by trip purpose • Vehicle trip origins and destinations Based on vehicle trips analysis, VMT calculations are performed for all cities within LA County (except for the City of Avalon), including unincorporated areas that are under direct County control. Using CARB Emissions Factors (EMFAC) model, CO2 and N2O emissions are estimated by multiplying emissions rates with vehicle activity data in all cities and unincorporated areas within the South Coast (SC) sub-area and the Mojave Desert (MD) sub-area. Sub-area emissions are then disaggregated based on speed bin by time of day and vehicle profile to estimate GHG emissions from into passenger vehicle and heavy duty trucks.

  • API

    Workforce Demographic Characteristics by Commuting Mode Split : 2012 - 2016

    data.cambridgema.gov | Last Updated 2019-09-17T17:17:39.000Z

    This data set provides demographic and journey to work characteristics of the Cambridge Workforce by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time arriving at work, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Workforce consist of all persons who work in Cambridge, regardless of home location. For more information on Journey to Work data in Cambridge, please see the full 2015 report: https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).

  • API

    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2014-06-10T19:28:50.000Z

    basic characteristics of people and housing for individual 2010 census block groups