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The population count of East South Central Division was 18,944,735 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.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Demographics and Population Datasets Involving East South Central Division

  • API

    AmeriCorps Member Race and Ethnicity National Figures

    data.americorps.gov | Last Updated 2021-02-06T01:05:53.000Z

    This dataset represents the percent distribution of AmeriCorps member terms which started their service in calendar year 2019 by race and ethnicity. This report excludes AmeriCorps Seniors volunteers. Included are percentage distributions from the United States Census Bureau's 2010-2019 State Population Characteristics dataset.

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    Texas Regional Economic Snapshots

    data.texas.gov | Last Updated 2020-06-26T23:40:44.000Z

    Find information on population, income, jobs, wages, graduation rates, highways, water and healthcare for the Comptroller's 12 Economic Regions. See https://comptroller.texas.gov/about/policies/privacy.php for more information on our agency’s privacy and security policies.

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    ARCHIVED - Leading Causes of Death in San Diego County

    internal-sandiegocounty.data.socrata.com | Last Updated 2023-04-25T17:32:22.000Z

    For current version see: https://www.sandiegocounty.gov/content/sdc/hhsa/programs/phs/community_health_statistics/CHSU_Mortality.html#leading Leading Causes of Death in San Diego County, by Gender, Race/Ethnicity, HHSA Region and Supervisorial District. Gender and race/ethnicity are at the county geographic level. Notes: 1. Rank is based on total number of deaths in each of the National Center for Health Statistics (NCHS) "rankable" categories. The top 15 leading causes of death presented here are based on the San Diego County residents for each year. 2. Cause of death is based on the underlying cause of death reported on death certificates as classified by ICD-10 codes. 3. Deaths for specific demographics or geographic area may not equal the total deaths for San Diego County due to missing data. § Not shown for fewer than 5 deaths. Source: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System. Prepared by County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2018.

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    NYSERDA Low- to Moderate-Income New York State Census Population Analysis Dataset: Average for 2013-2015

    data.ny.gov | Last Updated 2019-11-15T22:30:02.000Z

    How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).

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    Social Vulnerability Index for Virginia by Census Tract, 2018

    data.virginia.gov | Last Updated 2023-05-22T14:49:26.000Z

    "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

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    Hospital Inpatient Discharges (SPARCS De-Identified): 2014

    health.data.ny.gov | Last Updated 2019-09-13T16:31:56.000Z

    The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.

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    Hospital Inpatient Discharges (SPARCS De-Identified): 2013

    health.data.ny.gov | Last Updated 2019-09-13T19:04:24.000Z

    The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.

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    Hospital Inpatient Discharges (SPARCS De-Identified): 2012

    health.data.ny.gov | Last Updated 2019-09-13T16:29:09.000Z

    The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-Identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data contains basic record level detail regarding the discharge; however, the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.

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    Workforce Demographic Characteristics by Commuting Mode Split : 2012 - 2016

    data.cambridgema.gov | Last Updated 2023-08-01T12:47:27.000Z

    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 report Moving Forward: 2020 - https://www.cambridgema.gov/-/media/Files/CDD/FactsandMaps/profiles/demo_moving_forward_2020.pdf

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    Hospital Inpatient Discharges (SPARCS De-Identified): 2011

    health.data.ny.gov | Last Updated 2019-09-13T16:27:54.000Z

    The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, charges, and costs.This data contains basic record level detail regarding the discharge; however the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.