- What is the Population Rate of Change?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Student Teacher Ratio?
- What is the Median Earnings?
- What is the Mean Job Proximity Index?
- What is the Number of Employees?
- What is the Percent Without Health Insurance?
- What is the Mean Environmental Health Hazard Index?
The population count of Porter County, IN was 168,041 in 2018.
Demographics and Population Datasets Involving Porter County, IN
- API data.cityofnewyork.us | Last Updated 2020-02-08T00:56:30.000Z
Contains resident demographic data at a summary level as of January 1, 2019. The Resident Data Book is compiled to serve as an information source for queries involving resident demographic as well as a source of data for internal analysis. Statistics are compiled via HUD mandated annual income reviews involving NYCHA Staff and residents. Data is then aggregated and compiled by development. Each record pertains to a single public housing development.
- API opendata.maryland.gov | Last Updated 2019-12-13T12:53:02.000Z
Population profile - total, rate of change, age, and density.
- API health.data.ny.gov | Last Updated 2022-05-11T17:05:31.000Z
Population data file is provided as an additional reference file when interpreting vital statistics death rates. The population data is derived from the corresponding release of the NCHS annual estimates of "Bridged Race Vintage" which are consistent with the Bureau of the Census estimates from "Vintage" (released in the summer). For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/. The "About" tab contains additional details concerning this dataset.
Medicaid Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by Patient County: Beginning 2011health.data.ny.gov | Last Updated 2016-12-05T21:58:39.000Z
The datasets contain number of Medicaid PQI hospitalizations (numerator), county Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) for Medicaid enrollees beginning in 2011.
Hospital Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by County (SPARCS): Beginning 2009health.data.ny.gov | Last Updated 2020-11-16T17:30:46.000Z
This is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. This dataset is at the county level. The Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators (PQIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. All PQIs apply only to adult populations (over the age of 18 years). The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).
- API data.wa.gov | Last Updated 2021-09-01T17:20:31.000Z
Population and housing information extracted from decennial census Public Law 94-171 redistricting summary files for Washington state for years 2000 and 2010.
- API data.texas.gov | Last Updated 2022-03-21T14:05:59.000Z
As recommended by the Health and Human Services Commission (HHSC) to ensure consistency across all HHSC agencies, in 2012 DFPS adopted the HHSC methodology on how to categorize race and ethnicity. As a result, data broken down by race and ethnicity in 2012 and after is not directly comparable to race and ethnicity data in 2011 and before. The population totals may not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections data as of December 2020. Visit dfps.state.tx.us for information on all DFPS programs.
All Payer Potentially Preventable Emergency Visit (PPV) Rates by Patient County (SPARCS): Beginning 2011health.data.ny.gov | Last Updated 2018-01-24T16:43:17.000Z
The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011. The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up. The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient and outpatient data and Claritas population information. The observed, expected and risk adjusted rates for PPV are presented by either resident county (including a statewide total) or resident zip code (including a statewide total).
Hospital Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by Zip Code (SPARCS): Beginning 2009health.data.ny.gov | Last Updated 2020-11-16T17:30:46.000Z
This dataset is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).
- API data.ct.gov | Last Updated 2022-08-18T20:47:48.000Z
NOTE: As of 4/15/2021, this dataset will no longer be updated and will be replaced by two new datasets: 1) "COVID-19 Vaccinations by Town" (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town/x7by-h8k4) and "COVID-19 Vaccinations by Town and Age Group" (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town-and-Age-Group/gngw-ukpw). A summary of COVID-19 vaccination coverage in Connecticut by town. Records without an address could not be included in town vaccine coverage estimates. Total population estimates are based on 2019 data. A person who has received one dose of any vaccine is considered to have received at least one dose. A person is considered fully vaccinated if they have received 2 doses of the Pfizer or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. The number with At Least One Dose and the number Fully Vaccinated add up to more than the total number of doses because people who received the Johnson & Johnson vaccine fit into both categories. SVI refers to the CDC's Social Vulnerability Index - a measure that combines 15 demographic variables to identify communities most vulnerable to negative health impacts from disasters and public health crises. Measures of social vulnerability include socioeconomic status, household composition, disability, race, ethnicity, language, and transportation limitations - among others. Towns with a "yes" in the "Has SVI tract >0.75" field are those that have at least one census tract that is in the top quartile of vulnerability (e.g., a high-need area). 34 towns in Connecticut have at least one census tract in the top quartile for vulnerability. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected.