This map features new data from the US CDC, mapping Behavioral Risk Factors Data and Trends at the Census Tract level.For more info, see the CDC webpage on Chronic Disease and Health Promotion Data & Indicators: https://chronicdata.cdc.gov/health-area/behavioral-risk-factors.NMCDC has built the feature service that runs this map and made it available for sharing on your own AGOL map. It contains 27 adult behavioral risk factors for 206 census tracts in NM's four major cities (Albuquerque, Rio Rancho, Santa Fe and Las Cruces). Responses can be explored for two time periods (2014 and 2017), and trends over time are also dislayed.Feature service information at - https://nmcdc.maps.arcgis.com/home/item.html?id=2a261f56deb5452982233de0f87a6dd2#overview"The purpose of the 500 Cities Project is to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States. These small area estimates will allow cities and local health departments to better understand the burden and geographic distribution of health-related variables in their jurisdictions, and assist them in planning public health interventions. Learn more about the 500 Cities Project(https://www.cdc.gov/500cities/about.htm)."

Macro-enabled Excel file that can be used to (1) Link census tracts containing patient geocoded addresses to indicators of neighborhood crime and socioeconomic disadvantage using the census tract geoidentifier, and (2) Assign randomly generated identification numbers to census tracts and strip them of geoidentifiers to maintain patient confidentiality. (XLSM)

This map displays data from the Selected Economic Indicators (DP03) dataset from the 2010 American Community Survey 5-Yr Estimates, U.S. Census Bureau. Data is shown at the level of Census Tract, County, and Small Area (aggregation of Census Tracts developed by the New Mexico Department of Health). Measuring poverty is a topic of much current discussion. See the following links: A Different Way to Measure Poverty - http://www.sanders.senate.gov/imo/media/image/census.jpg"Few topics in American society have more myths and stereotypes surrounding them than poverty, misconceptions that distort both our politics and our domestic policy making."They include the notion that poverty affects a relatively small number of Americans, that the poor are impoverished for years at a time, that most of those in poverty live in inner cities, that too much welfare assistance is provided and that poverty is ultimately a result of not working hard enough. Although pervasive, each assumption is flat-out wrong." -Mark Rank, Professor of Social Welfare at Washington University: http://opinionator.blogs.nytimes.com/2013/11/02/poverty-in-america-is-mainstream/

A. SUMMARY It is the policy of the San Francisco Department of Public Health to comply with patient/client/resident rights regarding Protected Health Information (PHI) as set forth in the Health Insurance Portability and Accountability Act of 1996 (HIPAA). These guidelines exists to provide guidance only as it relates to the public release of COVID-19 data through the tracker webpages, so that public reporting of de-identified information of residents’ health status, demographic and other characteristics, and geographical information reflect consistent reporting practices and meaningful differences in health outcomes, conditions that impact health, and delivery of services while safeguarding patient/client/resident rights regarding PHI. COVID-19 related data will be released routinely in a variety of data products related to the tracker, including datasets through SF OpenData. Some data products may include data by county or smaller analysis unit such as ZIP code, neighborhood, or census tract. Download the attached PDF for the policy.

Resulting indices of the neighborhood risk environment in example multisite study.

The goal of the Justice40 Initiative is to provide 40 percent of the overall benefits of certain Federal investments in [eight] key areas to disadvantaged communities. These [eight] key areas are: climate change, clean energy and energy efficiency, clean transit, affordable and sustainable housing, training and workforce development, the remediation and reduction of legacy pollution, [health burdens] and the development of critical clean water infrastructure." Source: Climate and Economic Justice Screening toolJustice40 Tracts November 2022 Version 1.0 - Overview (arcgis.com)

This map features new data from the US CDC, mapping Behavioral Risk Factors Data at the Census Tract level for the first time.For more info, see the CDC webpage on Chronic Disease and Health Promotion Data & Indicators: https://chronicdata.cdc.gov/health-area/behavioral-risk-factors.NMCDC has built the feature service that runs this map and made it available for sharing on your own AGOL map. It contains 27 adult behavioral risk factors for 206 census tracts in NM's four major cities (Albuquerque, Rio Rancho, Santa Fe and Las Cruces). Feature service information at - http://nmcdc.maps.arcgis.com/home/item.html?id=bd74a088596e48358b22ae76a32a2631#overview "The purpose of the 500 Cities Project is to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States. These small area estimates will allow cities and local health departments to better understand the burden and geographic distribution of health-related variables in their jurisdictions, and assist them in planning public health interventions. Learn more about the 500 Cities Project(https://www.cdc.gov/500cities/about.htm)."

This map displays data from the Selected Economic Indicators (DP03) dataset from the 2010 American Community Survey 5-Yr Estimates, U.S. Census Bureau. Data is shown at the level of Census Tract, County, and Small Area (aggregation of Census Tracts developed by the New Mexico Department of Health). Measuring poverty is a topic of much current discussion. See the following links: A Different Way to Measure Poverty - http://www.sanders.senate.gov/imo/media/image/census.jpg"Few topics in American society have more myths and stereotypes surrounding them than poverty, misconceptions that distort both our politics and our domestic policy making."They include the notion that poverty affects a relatively small number of Americans, that the poor are impoverished for years at a time, that most of those in poverty live in inner cities, that too much welfare assistance is provided and that poverty is ultimately a result of not working hard enough. Although pervasive, each assumption is flat-out wrong." -Mark Rank, Professor of Social Welfare at Washington University: http://opinionator.blogs.nytimes.com/2013/11/02/poverty-in-america-is-mainstream/

Potential additional funds for each NM census tract if there is a complete count in the 2020 census. Includes locations of public places where neighborhood committees can conduct outreach and promotion to encourage community residents to respond. Potential outcomes for census dollars if there is a complete 2020 census count, based on the 2010 census mail return rates. Dollars are estimated for select populations (Poverty, LEP, Spanish LEP, Foreign Born) and for select federally funded programs whose funding amount is based off of population size and whose dollar amount is able to be calculated (Medicaid, Medicaid Part D, CHIP, Title IV Foster Care, Title IV Adoption Assistance, and the Child Care and Development Fund.) With places to do outreach in the community to encourage responses and get a complete count.

This map was updated in April of 2022. To see the archived version of this map, click here: https://nmcdc.maps.arcgis.com/home/item.html?id=2e4c4c4cafcc49db80837f32912e66a5#overviewThis map displays data from the Selected Economic Indicators (DP03) dataset from the 2020 American Community Survey 5-Yr Estimates, U.S. Census Bureau. Data is shown at the level of Census Tract and County levels. Small Areas are not on this map at this time (aggregation of Census Tracts developed by the New Mexico Department of Health). Measuring poverty is a topic of much current discussion. See the following links: A Different Way to Measure Poverty - https://www.sanders.senate.gov/imo/media/image/census.jpg"Few topics in American society have more myths and stereotypes surrounding them than poverty, misconceptions that distort both our politics and our domestic policy making."They include the notion that poverty affects a relatively small number of Americans, that the poor are impoverished for years at a time, that most of those in poverty live in inner cities, that too much welfare assistance is provided and that poverty is ultimately a result of not working hard enough. Although pervasive, each assumption is flat-out wrong." -Mark Rank, Professor of Social Welfare at Washington University: https://opinionator.blogs.nytimes.com/2013/11/02/poverty-in-america-is-mainstream/

Millions of Americans Are About to Lose Their Homes. Congress Must Help Them. -https://www.nytimes.com/2020/07/23/opinion/coronavirus-evictions-rent.html

MOST RECENT housing data is found in Feature Layer, "Selected Housing Characteristics, CENSUS TRACT, 2015 - DP04_2015_CT" - http://nmcdc.maps.arcgis.com/home/item.html?id=b9d9579a018f49748bbdbce921f991d9These data are currently being added to this map, Summer-Fall, 2017.This map displays data from the Selected Housing Characteristics (DP04) datasets American Community Survey 5-Yr Estimates, U.S. Census Bureau. Data is shown at the level of Census Tract, County, or Small Area (aggregation of Census Tracts developed by the New Mexico Department of Health). See recent data on Residential Vacancies (CT, HUD, 2014) LINKS (Older data):Feature Services: Selected Housing Characteristics by Census Tract 2010 - DP04a Selected Housing Characteristics by Census Tract 2010 - DP04b Selected Housing Characteristics by County 2010 - DP04a Selected Housing Characteristics by County 2010 - DP04b Selected Housing Characteristics by Small Area 2010 - DP04 Shapefiles: Selected Housing Characteristics by Census Tract 2010 - DP04a Selected Housing Characteristics by Census Tract 2010 - DP04b Selected Housing Characteristics by County 2010 - DP04a Selected Housing Characteristics by County 2010 - DP04b Selected Housing Characteristics by Small Area 2010 - DP04 Data Dictionaries (CSV): Data Dictionary for Selected Housing Characteristics by Census Tract 2010 - DP04 Data Dictionary for Selected Housing Characteristics by County 2010 - DP04 Data Dictionary for Selected Housing Characteristics by Small Area 2010 - DP04Selected Links on Affordable Housing:Rental Assistance Is Effective But Serves Only a Fraction of Eligible Households:http://www.cbpp.org/files/2-24-09hous-sec2.pdfCURRENT POPULATION REPORTS: http://www.census.gov/prod/1/pop/p25-1129.pdf

This map features new data from the US CDC, mapping Behavioral Risk Factors Data and Trends at the Census Tract level.For more info, see the CDC webpage on Chronic Disease and Health Promotion Data & Indicators: https://chronicdata.cdc.gov/health-area/behavioral-risk-factors.NMCDC has built the feature service that runs this map and made it available for sharing on your own AGOL map. It contains 27 adult behavioral risk factors for 206 census tracts in NM's four major cities (Albuquerque, Rio Rancho, Santa Fe and Las Cruces). Responses can be explored for two time periods (2014 and 2017), and trends over time are also dislayed.Feature service information at - https://nmcdc.maps.arcgis.com/home/item.html?id=2a261f56deb5452982233de0f87a6dd2#overview"The purpose of the 500 Cities Project is to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States. These small area estimates will allow cities and local health departments to better understand the burden and geographic distribution of health-related variables in their jurisdictions, and assist them in planning public health interventions. Learn more about the 500 Cities Project(https://www.cdc.gov/500cities/about.htm)."

This map features new data from the US CDC, mapping Behavioral Risk Factors Data and Trends at the Census Tract level.For more info, see the CDC webpage on Chronic Disease and Health Promotion Data & Indicators: https://chronicdata.cdc.gov/health-area/behavioral-risk-factors.NMCDC has built the feature service that runs this map and made it available for sharing on your own AGOL map. It contains 27 adult behavioral risk factors for 206 census tracts in NM's four major cities (Albuquerque, Rio Rancho, Santa Fe and Las Cruces). Responses can be explored for two time periods (2014 and 2017), and trends over time are also dislayed.Feature service information at - https://nmcdc.maps.arcgis.com/home/item.html?id=2a261f56deb5452982233de0f87a6dd2#overview"The purpose of the 500 Cities Project is to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States. These small area estimates will allow cities and local health departments to better understand the burden and geographic distribution of health-related variables in their jurisdictions, and assist them in planning public health interventions. Learn more about the 500 Cities Project(https://www.cdc.gov/500cities/about.htm)."

For information about the methodology used by the US Census, American Community Survey to estimate disability, see How Disability Data are CollectedABOUT THIS MAPThis version of the Disability Demographics map was created for the Los Alamos Lemonade Living project, Margi Harrach, Coordinator, info@lemonadeliving.org .Website: https://www.lemonadeliving.org/about_usA map for exploring the geographical distribution of disability in NM across a variety of boundaries (census tract, school, small area, county, house/senate district) to assist in estimating community numbers, program planning and gaps in services. Includes a sample of Children's Medical Service (CMS), as well as Family Infant and Toddler (FIT) program data. Originally produced for the 2014 Southwest Conference on Disability, this map has been updated a couple of times and is always open to feedback from potential collaborators and end-users.Suggestions, ideas, and input greatly appreciated.Map by Andrea CantareroContact - T Scharmen, thomas.scharmen@state.nm.us

This dataset provides 2018 Healthy Places Index (HPI) scores for each census tract in California as calculated by the Public Health Alliance of Southern California. The HPI is comprised of 25 individual indicators organized in 8 policy action areas (domains) of economy, education, healthcare access, housing, neighborhoods, clean environment, transportation, and social environment. Read the Healthy Places Index to learn more about index interpretation. Information like this may be useful for studying public health equity across areas of different socioeconomic demographics.Spatial Extent: CaliforniaSpatial Unit: Census TractCreated: 2018Updated: n/aSource: Public Health Alliance of Southern CaliforniaContact Telephone: Contact Email: PHASoCal@PHI.orgSource Link: https://healthyplacesindex.org/data-reports/

NMCDC Copy of Living Atlas map. Source: https://www.arcgis.com/home/item.html?id=23ab8028f1784de4b0810104cd5d1c8fIllustration by Brian BrenemanThis layer shows population broken down by race and Hispanic origin. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant race living within an area. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2013-2017ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 7, 2018National Figures: American Fact FinderThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This dataset is updated automatically when the most current vintage of ACS data is released each year. The service contains the ACS data as of the current vintage listed. Tabular data is updated annually with the Census Bureau's release schedule. This may alter data values, fields, and boundaries. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

National Risk Index Version: November 2021 (1.18.1)The National Risk Index Census Tracts feature layer contains Census tract-level data for the Risk Index, Expected Annual Loss, Social Vulnerability, and Community Resilience.The National Risk Index is a dataset and online tool to help illustrate the U.S. communities most at risk for 18 natural hazards: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. It was designed and built by FEMA in close collaboration with various stakeholders and partners in academia; local, state and federal government; and private industry. The Risk Index leverages available source data for natural hazard and community risk factors to develop a baseline relative risk measurement for each U.S. county and Census tract. The National Risk Index is intended to help users better understand the natural hazard risk of their communities.The National Risk Index provides relative Risk Index scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Geological Survey, California Office of Emergency Services, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA), Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability and Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute (HVRI).

A map for exploring the geographical distribution of disability in NM across a variety of boundaries (census tract, school, small area, county, house/senate district) to assist in estimating community numbers, program planning and gaps in services. Includes a sample of Children's Medical Service (CMS), as well as Family Infant and Toddler (FIT) program data. Originally produced for the 2014 Southwest Conference on Disability, this map has been updated a couple of times and is always open to feedback from potential collaborators and end-users.Suggestions, ideas, and input greatly appreciated.Andrea Cantareroandrea.cantarero@gmail.com720-877-6616

Map made for VIDA storymap, http://nmcdc.maps.arcgis.com/apps/Cascade/index.html?appid=a55bb730dbea4a5da9c706b748b72e44, for question/section 4: "What are the health conditions?"" showing health characteristics of remote small areas in New Mexico, including premature deaths by chronic disease deaths. Premature deaths is based off an average lifespan of 75 years.For more information on remote small areas in this context, please see story map at above link or see details at the source feature layer:Containing Rural areas as defined by US Census 2013 urban/rural defined areas, http://nmcdc.maps.arcgis.com/home/item.html?id=fbd1e91ec0a54c58b6fcca8a5138c1fc. Remote is filtered to include: 'RURAL' in 2 category designation, Population of LESS THAN 5001 persons, AND % Low access low-income at 20 miles to AT LEAST 5% for census tracts and small areas that contain a remote census tract are selected.