- Population
The population rate of change of 10509 ZIP Code was -2.19% in 2018.
Population
Population Change
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Demographics and Population Datasets Involving 10509 ZIP Code
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NYCHA Resident Data Book Summary
data.cityofnewyork.us | Last Updated 2020-02-08T00:56:30.000ZContains 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.
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Bronx Zip Population and Density
bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z2010 Census Data on population, pop density, age and ethnicity per zip code
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COVID-19 Vaccination Demographics in the United States,National
data.cdc.gov | Last Updated 2023-05-12T05:28:41.000ZOverall Demographic Characteristics of People Receiving COVID-19 Vaccinations in the United States at national level. Data represents all vaccine partners including jurisdictional partner clinics, retail pharmacies, long-term care facilities, dialysis centers, Federal Emergency Management Agency and Health Resources and Services Administration partner sites, and federal entity facilities.
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Medicaid Potentially Preventable Emergency Visit (PPV) Rates by Patient County: Beginning 2011
health.data.ny.gov | Last Updated 2016-12-16T15:57:37.000ZThe dataset contains Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for Medicaid beneficiaries by patient county 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.
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Medicaid Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by Patient County: Beginning 2011
health.data.ny.gov | Last Updated 2016-12-05T21:58:39.000ZThe 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.
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Chicago Population Counts
data.cityofchicago.org | Last Updated 2023-02-28T18:12:49.000ZPopulation totals for groupings commonly used in other datasets. Not all values are available for all years. Note that because the "Citywide" rows roll up the values from the individual ZIP Codes and the "Age 0-4," "Age 5-11," "Age 12-17," "Age 5+," "Age 18+," and "Age 65+" columns overlap other age categories, as well as each other in some cases, care should be taken in summing values to avoid accidental double-counting. The "Age 5-11" and "Age 12-17" columns only include children who live in households. Data Sources: U.S. Census Bureau American Community Survey (ACS) 5-year estimates (ZIP Code) and 1-year estimates (Citywide). The U.S. Census Bureau did not release standard 1-year estimates from the 2020 ACS. In 2020 only, 5-year estimates were used for the Citywide estimates.
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Hospital Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by Zip Code (SPARCS): Beginning 2009
health.data.ny.gov | Last Updated 2024-06-18T15:42:50.000ZThis 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).
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Medicaid Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by Patient Zip Code: Beginning 2011
health.data.ny.gov | Last Updated 2016-12-13T17:08:26.000ZThe 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.
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Indicators of Anxiety or Depression Based on Reported Frequency of Symptoms During Last 7 Days
data.cdc.gov | Last Updated 2024-10-04T14:06:38.000ZThe U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness. The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, gender, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions,
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All Payer Potentially Preventable Emergency Visit (PPV) Rates by Patient Zip Code (SPARCS): Beginning 2011
health.data.ny.gov | Last Updated 2024-07-19T16:07:58.000ZThe 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.