Indicator Data Sources

This page provides metadata for all of the indicators available in the Equity Atlas 2.0 mapping tool, including indicator descriptions, data sources, dates of the data, information about classification schemes and table attributes, and data limitations. It also includes links to additional spreadsheets that can be downloaded for further analysis as well as other relevant explanatory documentation.

Equity Atlas 2.0 Indicator Themes

Click on the theme to navigate to a list of indicators, metadata and data links for that theme.

COMMUNITY

DEMOCRATIC PARTICIPATION

DEMOGRAPHICS

ECONOMIC OPPORTUNITY

EDUCATION

FOOD

HEALTH CARE

HEALTH OUTCOMES

HEALTHY ENVIRONMENT

HOUSING

PARKS & NATURAL AREAS

SERVICES & AMENITIES

TRANSPORTATION

 


THEME: COMMUNITY

 

Other Relevant Indicators (not mapped)

  • Safety and Security
  • Culture
  • Social Capital
  • Stability
     

 


Community: Proximity to Faith-Based Institutions

Description: The Faith-Based Institutions indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes (1) establishments primarily engaged in operating religious organizations, such as churches, religious temples, and monasteries, and/or (2) establishments primarily engaged in administering an organized religion or promoting religious activities (813110).

Data Source: ESRI Business Analyst

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Proximity Raster (264' cell size)

Date of Data: 2010

Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

Rank
Description
1 Cells greater than 1 mile from a street.
2 Cells within 3/4 to 1 mile of a street.
3 Cells within 1/2 to 3/4 mile of a street.
4 Cells within 1/4 to 1/2 mile of a street.
5 Cells within 1/4 mile of a street.

Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations and institutions.

Link to Data [Excel Spreadsheet]

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Community: Proximity to Community Spaces and Indoor Gathering Places

Description: The Community Spaces and Indoor Gathering Places indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes civic and social organizations (813410) and coffee shops (722213) as well as schools, community centers and grange associations.

Data Source: ESRI Business Analyst, Metro RLIS

Data Limitations: These data sources do not capture the full range of community spaces and indoor gathering places available across the region. They represent the types of spaces for which comprehensive data is available. Mapping all the community spaces in every neighborhood across the region would require primary data collection at a scale that was not feasible for this project.

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Proximity Raster (264' cell size)

Date of Data: 2010 (Business Analyst); 2012 (RLIS)

Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

Rank
Description
1 Cells greater than 1 mile from a street.
2 Cells within 3/4 to 1 mile of a street.
3 Cells within 1/2 to 3/4 mile of a street.
4 Cells within 1/4 to 1/2 mile of a street.
5 Cells within 1/4 mile of a street.

Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations and institutions.

Link to Data [Excel Spreadsheet]

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Community: Community Stability (density of housing vacancies)

Description: The Community Stability indicator uses the U.S. Census data gathered on vacant units (all known addresses without occupants).

Data Source: U.S. Census 2010 (SF1); Universe = Households

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Density based on 2010 Census Blocks (264' cell size)

Date of Data: 2010

Map Classification Scheme (Density): Density rasters based on census blocks are displayed using a 1-5 classification scheme. Natural Breaks is used to create 5 classes based on the range of values. The Random Points tool is then used to distribute the values throughout the block area. The points are then rasterized using a 264 foot cell size. Blues represent low density. Browns represent high density.

Rank
Description
1 0% to 3.6% (low)
2 3.7% to 12.2% (medium low)
3 12.3% to 29.8% (medium)
4 29.9% to 68.4% (medium high)
5 68.5% to 100% (high)

Data Table Field Headings:Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet that includes the FIPS code (census block), State, County, Total Units, Total Occupied Units, Percent Occupied, Total Vacant Units, and Percent Vacant.

Link to Data [Excel Spreadsheet]

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Community: Proximity to Arts and Culture Institutions

Description: The Arts and Culture indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes Theater Companies and Dinner Theaters (711110), Dance Companies (711120), Musical Groups and Artists (711130), Other Performing Arts Companies (711190), Museums (712110), Historical Sites (712120), and Zoos and Botanical Gardens (712130) as well as a list of arts and culture organizations in Oregon provided by the Oregon Cultural Trust and a list of the location of street art provided by the Regional Arts and Culture Council (RACC). A list of additional arts and culture organizations in Clark County, Washington, was compiled by Arts of Clark County. Duplicates resulting from aggregation of these various data sources were removed in the dataset.

Data Source: ESRI Business Analyst, OR Cultural Trust, RACC, Arts of Clark County.

Data Limitations: This data is not an exhaustive list of arts and culture institutions and organizations but represents those for which data were available. In particular, it excludes informal arts and culture organizations, those without a physical location, and the many less institutionalized ways in which communities experience arts, culture, heritage, and creative expression.

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Proximity Raster (264' cell size)

Date of Data: 2010 (Business Analyst), 2012 (RACC, OR Cultural Trust, Arts of Clark County)

Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

Rank
Description
1 Cells greater than 1 mile from a street.
2 Cells within 3/4 to 1 mile of a street.
3 Cells within 1/2 to 3/4 mile of a street.
4 Cells within 1/4 to 1/2 mile of a street.
5 Cells within 1/4 mile of a street.

Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations, institutions and artists.

Link to Data [Excel Spreadsheet]

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Community: Proximity to Civic and Community Organizations

Description: The Civic and Community Organizations indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes civic and social organizations (813410), human rights organizations (813311), other social advocacy groups (813319), and other similar organizations (813990).

Data Source: ESRI Business Analyst

Data Limitations: These data sources do not capture the full range of civic and community organizations across the region. They represent the types of civic and community organizations for which comprehensive data are available. Mapping all of the civic and community organizations in every neighborhood across the region would require primary data collection at a scale that was not feasible for this project.

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Proximity Raster (264' cell size)

Date of Data: 2010

Map Classification Scheme (Proximity): Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

Rank
Description
1 Cells greater than 1 mile from a street.
2 Cells within 3/4 to 1 mile of a street.
3 Cells within 1/2 to 3/4 mile of a street.
4 Cells within 1/4 to 1/2 mile of a street.
5 Cells within 1/4 mile of a street.

Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations and institutions.

Link to Data [Excel Spreadsheet]

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Community: Proximity to Public Libraries

Description: The Public Libraries indicator is compiled from the Metro RLIS dataset.

Data Source: Metro RLIS (Places-Libraries)

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Proximity Raster (264' cell size)

Date of Data: July 2012

Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

Rank
Description
1 Cells greater than 1 mile from a street.
2 Cells within 3/4 to 1 mile of a street.
3 Cells within 1/2 to 3/4 mile of a street.
4 Cells within 1/4 to 1/2 mile of a street.
5 Cells within 1/4 mile of a street.

Data Table Field Headings: Summary tables for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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Description of Other Relevant Community Indicators (not mapped)

Safety and Security

Neighborhood safety is a critical quality of life issue. Many stakeholders emphasized the importance of mapping crime rates and/or calls to 911 as part of the Atlas’ analysis of community livability. Some stakeholders also suggested that this data should be counter-balanced by maps depicting racial profiling and police accountability issues. Unfortunately, while local police departments collect various types of crime rate data (as well as some data on police accountability), the data is not collected in a uniform way across jurisdictions. This makes it extremely difficult to meaningfully map this data at a regional scale.  For county-level crime and safety data, see the Greater Portland Pulse Website.

Culture

The Atlas includes data on the locations of formal arts and culture institutions, but this data does not adequately capture the full array of arts and culture in a community. Much of a community’s cultural life is reflected in more informal activities. The Urban Institute’s Arts and Culture Indicators in Community Building Project provides a set of guiding principles for conceptualizing the full extent of a community’s cultural life:

  • “Definitions of art, culture, and creativity depend on the cultural values, preferences, and realities of residents and other stakeholders in a given community.
  • The concept of participation includes a wide array of ways in which people engage in arts, culture, and creative expression.
  • Arts, culture, and creative expression are infused with multiple meanings and purposes simultaneously.
  • Opportunities for participation in arts, culture, and creative endeavor often rely on both arts-specific and non-arts-specific resources.”

This framework highlights the limitations of simply mapping formal arts and culture institutions. Unfortunately, however, these are the only cultural organizations for which data is easily available in a comprehensive way. Mapping the full extent of a community’s cultural life would require extensive ethnographic fieldwork that is beyond the scope of this project.

Social Capital

“Social capital” refers to the collective value of social networks and the benefits that arise from the existence of those social networks. Research has shown that communities with high levels of social capital are stronger, more resilient, have norms of mutual reciprocity and support, and are better positioned to engage in collective action to get things done. Research has also shown that on an individual level, having high levels of social capital can result in better health and quality of life. However, measuring social capital is a complex undertaking that requires in-depth research at a community level. For this reason, mapping social capital was beyond the scope of this project.

Stability

Neighborhood stability, as well as the stability of individual households, can contribute to stronger social networks, a greater sense of community, and increased livability. Residential stability can also result in better educational outcomes for children. One measure of the stability of a neighborhood is the length of time that residents have lived in the same place.  Unfortunately, the available data is not at a spatial resolution that lends itself to mapping this issue in a meaningful way.

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THEME: DEMOCRATIC PARTICIPATION
 

Other Relevant Indicators (not mapped)

  • Public Involvement Opportunities
  • Community Capacity
  • Government Responsiveness

Democratic Participation: Voter Registration Numbers

Description: The Voter Registration indicator shows the number of registered voters (regardless of party affiliation) aggregated to a 2010 census block group.

Data Source: Voter Activation Network

Data Limitations: Voter registration data does not always match the Census population/age data. It is possible some block groups indicate more registered voters than total population of voting age (although this is rare). This is likely due either to Census undercounting or because persons do not update their voter registration after a move to another precinct.

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Census Block Group 2010

Date of Data: 2012

Map Classification Scheme:
 

Class/Values Description
0 - 344 Number of registered voters in the block group.
345 - 785 Number of registered voters in the block group.
786 - 1282 Number of registered voters in the block group.
1283 - 2435 Number of registered voters in the block group.

Data Table Field Headings: Registered Voters, Voted in Last 3 Primaries or General Elections
 

Heading Description
FIPS FIPS code, block group.
Registered Total number of registered voters.
Pct_Gen_3 Total number of registered voters that voted in the last 3 general elections (2006, 2008 and 2010).
Pct_Pri_3 Total number of registered voters that voted in the last 3 primaries (2006, 2008 and 2010).

Link to Data [Excel Spreadsheet]

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Democratic Participation: Voter Participation Rates (primaries & general elections)

  • Voted in Last 3 Primaries
  • Voted in Last 3 General Elections

Description: The Voter Participation (voted in last 3 primaries or last 3 general elections) indicators show the percent of registered voters that voted in either the last 3 primary elections or the last 3 general elections. It is calculated by dividing the aggregate number of voters that submitted ballots in the referenced elections by the aggregate of registered voters for that year.

Data Source: Voter Activation Network

Data Limitations: Voter registration data does not always match the Census population/age data. It is possible some block groups indicate more registered voters than total population of voting age (although this is rare). This is likely due either to Census undercounting or because persons do not update their voter registration after a move to another precinct. Where errors in counts of registered voters occur, the percentage of eligible voters that voted in the last 3 primaries or general elections may be affected.

While voting in primary elections possibly indicates the most "active" voters, the pool of eligible voters is significantly less. For example, only voters indicating official party affiliation on their registration can vote in the party primary.

Both Oregon and Washington have vote-by-mail electoral systems. Care should be taken in comparing OR and WA voting rates with other states that have different systems.

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Census Block Group 2010

Date of Data: Midterm election in 2006, presidential/congressional election in 2008 and the midterm election in 2010.

Map Classification Scheme: Primary Elections
 

Class/Values Description
0% to 14.1% Percent of registered voters that voted in the last 3 primary elections.
14.2% to 20.4% Percent of registered voters that voted in the last 3 primary elections.
14.3% to 28.4% Percent of registered voters that voted in the last 3 primary elections.
28.5% to 49.8% Percent of registered voters that voted in the last 3 primary elections.

Map Classification Scheme: General Elections

Class/Values Description
8.2% to 35.2% Percent of registered voters that voted in the last 3 general elections.
35.3% to 46.2% Percent of registered voters that voted in the last 3 general elections.
46.3% to 56.2% Percent of registered voters that voted in the last 3 general elections.
56.3% to 100% Percent of registered voters that voted in the last 3 general elections.

Data Table Field Headings: Registered Voters, Voted in Primary and General Elections

Heading Description
FIPS FIPS code, block group.
Registered Total number of registered voters.
Pct_Gen_3 Percent of registered voters that voted in the last 3 general elections (2006, 2008 and 2010).
Pct_Pri_3 Total number of registered voters that voted in the last 3 primaries (2006, 2008 and 2010).

Link to Data [Excel Spreadsheet]

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Description of Other Relevant Democratic Participation Indicators (not mapped)

A core component of the Regional Equity Atlas 2.0 definition of equity is that “all people have the power to shape the future of their communities through public decision-making processes that are transparent, inclusive, and engage the community as full partners.” However, as essential as this issue is to the mission of the Equity Atlas, it is unfortunately not an issue that lends itself to being mapped. The indicators listed below summarize the kinds of information that could be measured in order to map this issue. But despite significant work to try to identify potential methodologies and data sources for mapping these indicators, none of them ultimately turned out to be mappable because data is not collected on these issues in a systematic way.

Public Involvement Opportunities

A key measure of democratic participation in local decision-making is whether a jurisdiction or decision-making body provides meaningful opportunities for impacted communities to have input into the decisions affecting their lives. This includes:

  • Do people know about the upcoming decision and how to impact it? For example, is outreach conducted to inform the community about the decision? Is information about the proposed project, policy, or plan made publicly available in an easily located and navigable way?
  • Do decision-making processes ensure adequate opportunities for community input in ways that are open to the public and fair and transparent?
  • Do decision-makers invest in strategies to reduce common barriers to participation by providing resources for translation and interpretation, child care, transportation, and selecting times and locations of meetings that are broadly accessible?
  • Does local government support leadership development and capacity building of diverse populations, including under-represented groups? Is this reflected in the diversity of leadership in advisory committees and other participatory decision-making bodies?

Community Capacity

In order to impact decision-making, the community needs to have the capacity to take collective action to identify residents’ priorities and then influence decision-making to reflect these priorities. Key measures of community capacity include:

  • Does the community have neighborhood associations and community organizations that are capable of representing community members’ interests in a democratic and inclusive way? For example, do these organizations have regularly scheduled open meetings that are widely announced and broadly accessible? Do they have regular outreach and communication mechanisms? Do they have a diverse membership that is reflective of the demographics of the broader community?
  • Do these organizations have the information, social connections, skills, and capacity to be able to bring residents together to effectively solve problems and achieve their common aspirations?
  • Do these organizations have formal recognition by local decision-makers and opportunities for a seat at the table in public decisions?

Government Responsiveness

Community action may not be very effective if government is not willing to listen and meaningfully respond to community input. Key measures of government responsiveness include:

  • Is there a culture within local government that supports a commitment to public involvement?  For example, do government agencies and decision-making bodies have formal public involvement policies that specify how public input will be gathered and incorporated into specific decisions?
  • Are decisions made through an open process in which community input is heard and given serious consideration?
  • Do decision-makers circle back to the community to explain the decisions that were made, the rationale for the decisions, and how community input was used?

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THEME: DEMOGRAPHICS

 

Population Density

Age

Race/Ethnicity

Income

Household Composition

Immigrants

Veterans

Population Overlays

Change Over Time Indicators (not mapped in this iteration of the tool):

  • Change in Population Density (2000-2010 and 1990-2000)
  • Change in Hispanic Population (2000-2010 and 1990-2000)
  • Change in African-American Population (2000-2010 and 1990-2000)
  • Change in Asian Population (2000-2010 and 1990-2000)
  • Change in Native American and Alaskan Native Population (2000-2010 and 1990-2000)
  • Change in Hawaiian and Pacific Islander Population (2000-02010) NOTE: This category was included in the Asian category in the 1990 US Census -- calculating change from 1990-2000 is not possible.
  • Change in Distribution of Age Under 5 (2000-2010 and 1990-2000)
  • Change in Distribution of Age 65 and Above (2000-2010 and 1990-2000)

Other Relevant Indicators (not mapped)

  • Persons with Disabilities

Demographics: Population Density

  • Residential Density
  • Employee Density
  • Total Population Density (Residents + Employees)

Description: Population Density consists of three indicators that show the density of residents, employees and a combination of residents and employees.

Data Source: ESRI Business Analyst, US Census, Metro Databases

Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

Geographic Unit: Density Raster (264' cell size)

Date of Data: 2010

Data Processing: Density of employees was derived from ESRI’s Business Analyst employment data points.  The number of employees was used as the point weighting to create a density surface.  Most were geocoded to parcels although some were coded to street centerlines and the few PO boxes were coded to zipcode points.

Calculating density of residents was a multistep process.  Taxlots classified by the County Assessors as SFR (Single-Family Residence) -- as well as AGR, RUR, and FOR taxlots with building values (agriculture, rural and forest) were selected and converted to points (centroids).  Any points that intersected the RLIS multifamily database (mostly condos) were deleted so they weren’t double-counted. The RLIS multifamily database was converted to points and merged. All points were intersected with 2010 Census Blocks and assigned average household size based on the type of point (single vs. multifamily) to derive persons per point. These were totaled and the totals were then checked against the actual census numbers for the block.  Corrections applied a factor to adjust to 2010 population numbers. The corrected population numbers per point were then used to generate a density surface using the Kernel Density tool.

The Density of Residents & Employees adds the two datasets together.

Map Classification Scheme (Density): Density rasters based on population are displayed using a 1-5 classification scheme. Blues represent low density. Browns represent high density.

Rank Description
1 Low density.
2 Medium-low density.
3 Medium density.
4 Medium-high density.
5 High density.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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    Demographics: Age

    Description: The Age indicators show the density (persons per acre) of various aggregated age categories including young and school-age children (Under 5, 5-17, and 0-17), adults (18-44 and 45-64) and seniors (65 and over).

    Data Source: U.S. Census 2010 (P12 Sex by Age); Universe = Total Population

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Density Raster (264' cell size)

    Date of Data: 2010

    Data Processing: An "ecumene" mask was created to remove areas of no residential population prior to creating the rasters. Click on the link below for a slideshow documenting how the census rasters were processed.

    Census Rasters Data Processing Slideshow

    Map Classification Scheme (Density): Density rasters based on census block data are displayed using a 1-5 classification scheme. For the Age rasters, a ranking of 1 is always used to indicate cells with no residential population or no population of the age range displayed. Natural Breaks is used to create the remaining 4 classes (ranked 2-5) based on the range of values. Blues represent low density. Browns represent high density.

    Classification Scheme Limitations: The classification schemes between the various age indicators are relative rather than absolute (or standardized). This means that a classification of “5” in the Under 5 map, while it represents the areas with the highest densities of children under 5 in the Metro region, does not represent the same range of values as the areas classified a “5” in the 65 and Over indicator. Therefore, it is not advisable to make side-by-side comparisons between the age maps. They should be used independently.

    Age 0-4 (population density per acre)

    Rank Description
    1 No population (either no residents or no population in the Under 5 age range).
    2 .09 to .61
    3 .62 to 1.6
    4 1.7 to 3.6
    5 3.7 to 22

    Age 5-17 (population density per acre)

    Rank Description
    1 No population (either no residents or no population in the 5-17 age range).
    2 .21 to 1.1
    3 1.2 to 2.8
    4 2.9 to 5.9
    5 6 to 54

    Age 0-17 (population density per acre)

    Rank Description
    1 No population (either no residents or no population in the 0-17 age range).
    2 .23 to 1.4
    3 1.5 to 3.7
    4 3.8 to 8.5
    5 8.6 to 59

    Age 18-44 (population density per acre)

    Rank Description
    1 No population (either no residents or no population in the 18-44 age range).
    2 .66 to 4
    3 4.1 to 11
    4 12 to 30
    5 31 to 170

    Age 45-64 (population density per acre)

    Rank Description
    1 No population (either no residents or no population in the 45-64 age range).
    2 .28 to 1.4
    3 1.5 to 3.4
    4 3.5 to 14
    5 15 to 72

    Age 65 and Over (population density per acre)

    Rank Description
    1 No population (either no residents or no population in the 65 and Over age range).
    2 .41 to 1.6
    3 1.7 to 7.4
    4 7.5 to 33
    5 34 to 100

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet for the full dataset that includes the FIPS code and numbers/percents for all age categories.

    Link to Data [Excel Spreadsheet]

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    Demographics: Race/Ethnicity

    Description: The Race & Ethnicity indicators show the density (per acre) of populations of race and ethnic categories tracked by the U.S. Census including Hispanic, African American, Asian, Native American/Alaskan Native, and Native Hawaiian/Pacific Islander. For the purpose of Equity Atlas 2.0, Hispanic is considered a race category as well. Populations of Color is an aggregate of all race/ethnic categories (excluding white non-hispanic).

    NOTE: The 2010 census race/ethnicity categories represent an "overcount" -- if one census respondent checked three race categories, he/she would be counted three times (once in each race). Populations of Color, however, represent all persons excluding white, non-hispanic and is thus not an overcount.

    Data Source: U.S. Census 2010 (QT-P6 Race Alone or in Combination and Hispanic or Latino); Universe = Total Population

    Data Limitations: The categories used in the U.S. Census for collecting information on race and ethnicity do not capture the wide range of racial and ethnic identities within the population. For example, African communities are considered within the Census categories to be “Black/African American”; Slavic and Middle Eastern communities are typically counted as “White”; the category “Asian” includes a wide array of different nationalities and cultural identities; etc. Requiring respondents to define themselves using the federal categories renders some populations invisible. Furthermore, people of color have historically been under-counted by the Census, American Community Survey, and other government enumeration efforts. This is due to a variety of reasons. For example, legacies of mistrust and the historic marginalization of some communities of color by mainstream agencies may lead to lower participation rates; language barriers can reduce participation rates among immigrant communities; housing instability can make it more difficult for enumeration efforts to reach some residents; etc. Because of these dynamics, many researchers and advocates caution that Census demographic data do not provide an accurate representation of population demographics, particularly among communities of color and immigrant populations.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Density Raster (264' cell size)

    Date of Data: 2010

    Data Processing: An "ecumene" mask was created to remove areas of no residential population prior to creating the rasters for race and ethnic populations. Click on the link below for a slideshow documenting how the census rasters were processed.

    Census Rasters Data Processing Slideshow

    Map Classification Scheme (Density): Density rasters based on census block data are displayed using a 1-5 classification scheme. For the Race/Ethnicity rasters, a ranking of 1 is always used to indicate cells with no residential population or no population of the race being displayed. Natural Breaks is used to create the remaining 4 classes (ranked 2-5) based on the range of values. Blues represent low density. Browns represent high density.

    Classification Scheme Limitations: The classification schemes between the various race/ethnic indicators are relative rather than absolute (or standardized). This means that a classification of “5” in the Pacific Islander map, while it represents the areas with the highest densities of Pacific Islanders in the Metro region, does not represent the same range of values as the areas classified a “5” in the African American indicator. Therefore, it is not advisable to make side-by-side comparisons between the race maps. They should be used independently.

    Hispanic (population density per acre)

    Rank Description
    1 No population (either no residents or no population of Hispanics).
    2 0.3 to 2.1
    3 2.2 to 7.5
    4 7.6 to 20
    5 21 to 77

    African-American (population density per acre)

    Rank Description
    1

    No population (either no residents or no population of African-American).

    2 .16 to 1.5
    3 1.6 to 5.4
    4 5.5 to 16
    5 17 to 42

    Asian (population density per acre)

    Rank Description
    1 No population (either no residents or no population of Asian).
    2 .19 to 1.1
    3 1.2 to 3.3
    4 3.4 to 8.9
    5 9 to 47

    Native American and Alaskan Native (population density per acre)

    Rank Description
    1 No population (either no residents or no population of Native American or Alaskan Native).
    2 .05 to .36
    3 .37 to .91
    4 .92 to 2.1
    5 2.2 to 12

    Hawaiian and Pacific Islander (population density per acre)

    Rank Description
    1 No population (either no residents or no population of Hawaiian/Pacific Islander).
    2 .06 to .38
    3 .39 to 1.1
    4 1.2 to 3.3
    5 3.4 to 16

    Populations of Color (population density per acre)

    Rank Description
    1 No population (either no residents or no populations of color).
    2 .47 to 2.8
    3 2.9 to 7.9
    4 8 to 20
    5 21 to 120

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet for the full dataset that includes the FIPS code and numbers/percents for all race/ethnicity categories.

    Link to Data [Excel Spreadsheet]

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    RACE/ETHNICITY: PERCENT CHANGE IN POPULATIONS OF COLOR (2000-2010)

    Description: The Percent Change in Populations of Color indicator shows the rate of change between 2000 and 2010 for the population identifying as anything except “white, non-Hispanic” by census tract.  This “populations of color” category was derived by subtracting the white, non-Hispanic population from the total population of each census tract.  The rate of change was then calculated by subtracting the 2000 populations of color from the 2010 populations of color and then dividing this number by the 2000 populations of color. 

    The geometries of some census tracts in the greater Portland area changed from 2000 to 2010 (due to tract splits or, in a few cases, merges). The values were also split or merged prior to calculating the change over time based on a value proportion. The example below illustrates the calculation:

    In 2000, Tract #1 had 100 persons.
    In 2010, the tract was split into #2 (with 150 persons) and #3 (with 100 persons) for a total of 250 persons.
    Tract #2 represents 60% of the 2010 total and Tract #3 represents 40% of the 2010 total.
    Assign a 2000 value of 60 persons (60% of 100) in Tract #2 and 40 persons (40% of 100) in Tract #3.
    Subtract 2000 value from 2010 value.

     

    Data Source: U.S. Census 2000 and 2010 (QT-P6 Race Alone or in Combination and Hispanic or Latino); Universe = Total Population

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Census Tracts 2010

    Date of Data: 2000 and 2010

    Map Classification Scheme: Six classes based on the natural breaks in the value range with class breaks delineating positive and negative change.

    Class/Values Description
    -96% to -43% Percent decline in Populations of Color.
    -42% to -25% Percent decline in Populations of Color.
    -24% to -1% Percent decline in Population of Color.
    0% to 50% Percent gain in Populations of Color.
    51% to 100% Percent gain in Populations of Color.
    101% to 640% Percent gain in Populations of Color.

    Data Table Field Headings:

    Heading Description
    ID FIPS code (tract 2000)
    TOTPOP Total Population 2010
    Rate_NWPop Rate of Change (2000-2010)
    NW_2000 Non-White Population (2000)
    NW_2010 Non-White Population (2010)

    Link to Data [Excel Spreadsheet]

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    Demographics: Income

    Description: Income consists of four indicators that explore average income, poverty, and change over time. The data sources and geographic units vary and are outlined below.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)
     

    INCOME: MEDIAN INCOME (ACS 2006-2010 Estimate)

    Description: The Median Income indicator represents the average (median) income for families for each census tract.

    Data Source: American Community Survey (ACS 2006 to 2010 estimate); S1903 (Median Income in the Past 12 Months in 2010 Inflation-Adjusted Dollars)

    Data Limitations: The ACS uses a sample survey. The margin of error can be high in tracts with a low sample population. The margin of error and coefficient of variation are provided in the [Link to Data] below and should be consulted before any analysis. For more information on using ACS data click on the link below.

    ACS Policy Brief

    Geographic Unit: Census Tracts 2010

    Date of Data: ACS 5-Year Estimate (2006-2010)

    Map Classification Scheme: Four classes based on natural breaks. The 2010 median household income for the 4-county metropolitan region as a whole is $56,722.
     

    Class/Values Description
    $14,960 to 55,208 Median income range.
    $55,209 to 76,754 Median income range.
    $76,755 to 103,142 Median income range.
    $103,143 to 154,466 Median income range.

    Data Table Field Headings:

    Heading Description
    ID FIPS code (census tracts).
    FAMINC Median Family Income.
    PFamBelow Percent of Families below Federal Poverty Threshold.

    Link to Data [Excel Spreadsheet]

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    INCOME: PERCENT CHANGE IN MEDIAN INCOME (2000 to 2006-2010 Estimate)

    Description: This map represents the change in median income for households from 2000 to the ACS 2006 to 2010 estimate for each census tract and ranges from negative change (a decline in the median income) to positive change (a gain in median income).

    Data Source: American Community Survey (ACS); 2000 (P077 Median Family Income) and 2006 to 2010 estimate (S1903 Median Income in the Past 12 Months for Households, Families, and Non-Families).

    Data Limitations: The ACS uses a sample survey. The margin of error can be high in tracts with a low sample population. The margin of error and coefficient of variation are provided in the [Link to Data] below and should be consulted before any analysis. For more information on using ACS data click on the link below.

    ACS Policy Brief

    Geographic Unit: Census Tracts 2010

    Date of Data: 2000 (sampled data) and ACS 5-Year Estimates (2006-2010)

    Data Processing: Median income for 2000 and the ACS 2006 to 2010 estimates were retrieved from the ACS. The 2000 median income was adjusted for inflation (multiplier = 1.2533 based on inflation rates provided by the Department of Labor). For census tracts that changed (split) between 2000 and 2010, the same 2000 median income was assigned to each of the split 2010 tracts (under the assumption that an "average" is representative of the entire geographic unit). The difference between adjusted 2000 and 2006-2010 estimated median income for each 2010 tract was computed.  The rate of change was then calculated by subtracting the 2006 to 2010 estimated median income from the adjusted 2000 median income and then dividing this number by the 2000 median income. 

    Map Classification Scheme: Five classes based on natural breaks with class breaks delineating positive and negative change.

    Class/Values Description
    -55.49% to -15% Large decline in median income.
    -14.99% to -0.01% Moderate decline in median income.
    0.02% to 20% Small gain in median income.
    20.01% to 50% Moderate gain in median income.
    50.01% to 187.92% Large gain in median income.

    Data Table Field Headings: The field headings in the table below are those found in the online map's attribute table. The [Link to Data] below downloads an Excel spreadsheet that lists the margin of error and coefficient of variation and also documents the census tracts that changed from 2000 to 2010.

    Heading Description
    ID FIPS code (census tracts 2010).
    MEDINC00 Median Family Income (2000).
    INC00ADJ 2000 Median Family Income Adjusted for Inflation.
    MEDINC10 Median Family Income (2010).
    INCMOE10 2010 Median Family Income Margin of Error.
    CHANGE Rate of Change between 2000 and 2010 Median Family Income.

    Link to Data [Excel Spreadsheet]

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    INCOME: PERCENT HOUSEHOLDS BELOW POVERTY LEVEL (2006 to 2010 Estimate)

    Description: The Households Below Poverty indicator shows the percentage of households below the federal poverty level in each census tract.

    Data Source: American Community Survey (ACS 2006 to 2010 estimates); S1701 (Poverty Status in the Past 12 Months)

    Data Limitations: The Census definition of poverty, originally developed in the early 1960s, is widely criticized for setting the poverty threshold at an unrealistically low level. The Census definition calibrates the poverty level as a function of food costs. However, in contrast to the 1960s, a bigger share of a family's paycheck today goes to items such as housing, child care, transportation and health care compared with food.

    The ACS uses a sample survey. The margin of error can be high in tracts with a low sample population. For more information on using ACS data and how the U.S. Census measures poverty click on the links below.

    ACS Policy Brief

    How the U.S. Census Measures Poverty

    Geographic Unit: Census Tracts 2010

    Date of Data: ACS 5-Year Estimates (2006-2010)

    Map Classification Scheme: Four classes based on natural breaks.
     

    Class/Values Description
    0% to 5.7% Low rates of poverty.
    5.8% to 12.7% Medium-low rates of poverty.
    12.8% to 22.9% Medium rates of poverty.
    23% to 50.6% High rates of poverty.

    Data Table Field Headings:

    Heading Description
    ID FIPS code (census tracts).
    FAMINC Median Family Income.
    PFamBelow Percent of Families below Federal Poverty Threshold.

    Link to Data [Excel Spreadsheet]

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    INCOME: PERCENT OF STUDENTS ELIGIBLE FOR FREE OR REDUCED COST LUNCH

    Description: The Students Eligible for Free or Reduced Cost Lunch indicator shows the percentage of K-12 students taking part in the free and reduced cost lunch program. This indicator is often used as a proxy for childhood poverty.

    Data Source: OR Department of Education (ODE); WA Office of the Superintendent of Public Instruction (WAOSPI)

    Geographic Unit: Graduated Points (by school)

    Date of Data: 2011-12 Academic Year

    Map Classification Scheme: Four classes based on natural breaks.
     

    Class/Values Description
    2% to 30% Percent of students participating in the free or reduced cost lunch program.
    31% to 45% Percent of students participating in the free or reduced cost lunch program.
    46% to 70% Percent of students participating in the free or reduced cost lunch program.
    71% to 95% Percent of students participating in the free or reduced cost lunch program.

    Data Table Field Headings:

    Heading Description
    NAME Name of School
    LEVEL

    Grade Level of School

    • Elementary
    • Middle or Junior High
    • High School
    • Various Grade Levels
    • Skill Center or Alternative
    • Special
    FREELUNCHP Percent of Students Participating in the Free or Reduced Cost Lunch Program

    Link to Data [Excel Spreadsheet]

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    Demographics: Household Type

    • Households with No Children
    • Families with Children
    • Single Parent Families

    Description: The Household Type indicators show the density (households per acre) of various household categories including adults with no children, families, and single parent families (a subset of families).

    Data Source: U.S. Census 2010 (P19 Household Type); Universe = Total Households

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Density Raster (264' cell size)

    Date of Data: 2010

    Data Processing: An "ecumene" mask was created to remove areas of no residential population prior to creating the rasters. Click on the link below for a slideshow documenting how the census rasters were processed.

    Census Rasters Data Processing Slideshow

    Map Classification Scheme (Density): Density rasters based on census block data are displayed using a 1-5 classification scheme. For the Household Type rasters, a ranking of 1 is always used to indicate cells with no residential population or no value for the household type displayed. Natural Breaks is used to create the remaining 4 classes (ranked 2-5) based on the range of values. Blues represent low density. Browns represent high density.

    Classification Scheme Limitations: The classification schemes between the various household indicators are relative rather than absolute (or standardized). This means that a classification of “5” in the Families map, while it represents the areas with the highest densities of families in the metro region, does not represent the same range of values as the areas classified a “5” in the Single-Parent Families indicator. Therefore, it is not advisable to make side-by-side comparisons between the age maps. They should be used independently.

    Families with Children (population density per acre)

    Rank Description
    1 No residential population.
    2 .1 to 1
    3 2 to 3
    4 4 to 6
    5 7 to 30

    Adults with No Children (population density per acre)

    Rank Description
    1 No residential population.
    2 .47 to 3.3
    3 3.4 to 12
    4 13 to 37
    5 38 to 120

    Single Parent Families (population density per acre)

    Rank Description
    1 No residential population.
    2 .05 to .44
    3 .45 to 1.2
    4 1.3 to 2.7
    5 2.8 to 14

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet that includes the FIPS code and numbers/percents for all household types.

    Link to Data [Excel Spreadsheet]

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    Demographics: Immigrants

    Description: The Immigrants indicators draw upon available census information about the immigrant population including recent immigrants (entered country 2000 or later), percent of foreign-born population and households with low English proficiency.

    IMMIGRANTS: PERCENT FOREIGN BORN

    Description: This indicator shows the percent of the population that is foreign-born. Foreign born includes both naturalized citizens and non-citizens.

    Data Source: American Community Survey (ACS 2006 to 2010 estimate); DP02 Selected Social Characteristics

    Data Limitations: Because of sample size issues, the margin of error tends to be quite high when disaggregating ACS data. Consequently, the immigrant indicators are mapped at the PUMA level -- a relatively coarse geographic unit, but one where the margin of errors are at an acceptable level. The maps can be used to discern general regional patterns only.

    The attribute table contains information on the margin of error and should be consulted before using this data for any analyses. Data can be downloaded using the link below.

    Immigrant populations are likely to be under-represented in American Community Survey data due to a range of factors including language barriers and distrust of government among some immigrant groups based on their experiences in their countries of birth.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: PUMA 2010

    Date of Data: ACS 5-Year Estimates (2006-2010)

    Map Classification Scheme:

    Class/Values Description
    5.6% to 9% Percent of population that is foreign-born.
    9.1% to 14.6% Percent of population that is foreign-born.
    14.7% to 21.5% Percent of population that is foreign-born.

    Data Table Field Headings:

    Heading Description
    PUMA PUMA ID
    ForBorn Number of foreign born.
    ForBornMOE Foreign born margin of error.
    PForBorn Foreign born as a percent of total population.
    PFBornMOE Foreign born percent margin of error.

    Link to Data [Excel Spreadsheet]

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    IMMIGRANTS: PERCENT RECENT IMMIGRANTS (2000 AND LATER)

    Description: The Recent Immigrants indicator shows the percent of foreign-born citizens with a year of entry 2000 or later.

    Data Source: American Community Survey (ACS 2006-2010 Estimates); DP02 Selected Social Characteristics

    Data Limitations: Because of sample size issues, the margin of error tends to be quite high when disaggregating ACS data. Consequently, the immigrant indicators are mapped at the PUMA level -- a relatively coarse geographic unit, but one where the margin of errors are at an acceptable level. The maps can be used to discern general regional patterns only.

    The attribute table contains information on the margin of error and should be consulted before using this data for any analyses. Data can be downloaded using the link below.

    Immigrant populations are likely to be under-represented in American Community Survey data due to a range of factors including language barriers and distrust of government among some immigrant groups based on their experiences in their countries of birth.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: PUMA 2010

    Date of Data: ACS 5-Year Estimates (2006-2010)

    Map Classification Scheme:

    Class/Values Description
    18.5% to 18.8% Percent of foreign-born citizens with year of entry 2000 or later.

    18.9% to 31.5%

    Percent of foreign-born citizens with year of entry 2000 or later.
    31.6% to 37.9% Percent of foreign-born citizens with year of entry 2000 or later.

    Data Table Field Headings:

    Heading Description
    PUMA PUMA ID
    ForBor00 Number of foreign-born citizens with year of entry 2000 or later (recent immigrants).
    ForBor00MO Recent immigrants MOE.
    PForBor00 Percent of foreign-born citizens with year of entry 2000 or later (percent recent immigrants).
    PForBor00M Percent recent immigrants MOE.

    Link to Data [Excel Spreadsheet]

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    IMMIGRANTS: PERCENT HOUSEHOLDS WITH LOW ENGLISH PROFICIENCY

    Description: The Low English Proficiency indicator shows the percent of the population over 5 years old with low English proficiency. Low English proficiency is determined through a ranked question that asks whether a person can speak English very well to none at all. The map shows the population (over 5) that can speak English not at all or less than very well.

    Data Source: American Community Survey (ACS 2006-2010 Estimates); DP02 Selected Social Characteristics

    Data Limitations:Because of sample size issues, the margin of error tends to be quite high when disaggregating ACS data. Consequently, the immigrant indicators are mapped at the PUMA level -- a relatively coarse geographic unit, but one where the margin of errors are at an acceptable level. The maps can be used to discern general regional patterns only.

    The attribute table contains information on the margin of error and should be consulted before using this data for any analyses. Additional data can be downloaded using the link below.

    Immigrant populations are likely to be under-represented in American Community Survey data due to a range of factors including language barriers and distrust of government among some immigrant groups based on their experiences in their countries of birth.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: PUMA 2010

    Date of Data: ACS 5-Year Estimates (2006-2010)

    Map Classification Scheme:

    Class/Values Description
    3% to 5% Percent of population over 5 years that speak English less than "very well."
    6% to 8% Percent of population over 5 years that speak English less than "very well."
    9% to 18% Percent of population over 5 years that speak English less than "very well."

    Data Table Field Headings:

    Heading Description
    PUMA PUMA ID
    LowEngl Number of population over 5 years that speak English less than "very well" (Low English Proficiency).
    LowEnglMOE Population with low English proficiency MOE.
    PLowEngl Percent of population with low English proficiency.
    PLowEnglMO Percent of population with low English proficiency MOE.

    Link to Data [Excel Spreadsheet]

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    Demographics: Veterans

    Description: The Veterans indicator shows the percent of the civilian population 18 years or older that has veteran status. Veteran status, according to the census definition, includes men and women who have served (even for a short time) in the military, but are not currently on active duty (Army, Navy, Air Force, Marine Corps, Coast Guard). Those who served in the National Guard or Reserves are classified as veterans only if they were ordered to active duty for a military campaign at any time (not counting the 4-6 months for initial training or required weekend/summer deployments).

    Data Source: American Community Survey (ACS 2006-2010 estimates); DP02 Selected Social Characteristics

    Data Limitations: Because of sample size issues, the margin of error tends to be quite high when disaggregating ACS data. Consequently, the veterans indicator is mapped at the PUMA level -- a relatively coarse geographic unit but one where the margin of errors are at an acceptable level. The map can be used to discern general regional patterns only.

    The attribute table downloadable from the link below contains information on the margin of error and should be consulted before using this data for any analyses.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: PUMA 2010

    Date of Data: ACS 5-Year Estimates (2006-2010)

    Map Classification Scheme:
     

    Class/Values Description
    7% to 8% Percent of civilian population 18 years and older with veteran status.
    9% to 11% Percent of civilian population 18 years and older with veteran status.
    12% to 16% Percent of civilian population 18 years and older with veteran status.

    Data Table Field Headings:

    Heading Description
    ID2 PUMA ID
    PVets Percent of civilian population 18 years and older with veteran status.

    Link to Data [Excel Spreadsheet]

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    Demographics: Population Overlays

    Description: The Population Overlays identify those census tracts that are above or below regional averages in measures that isolate various categories of the population. These indicators are designed to be used as overlays with other indicators, to quickly locate areas of interest (high percentages of a population category). There are five Population Overlays:

    • Above Regional Average Percent Populations of Color
      • Regional 2010 Median Percent = 20.75%
    • Above Regional Average Percent Populations in Poverty
      • Regional 2010 Median Percent = 6.73%
    • Below Regional Median Income
      • Regional 2010 Median Income = $56,722
    • Above Regional Average Percent Youth (Ages 0-17)
      • Regional 2010 Median Percent = 23.68%
    • Above Regional Average Percent Seniors (Ages 65 and Over)
      • Regional 2010 Median Percent = 10.76%

    Data Source: U.S. Census 2010 (Race and Age); American Community Survey 5-Year Estimates 2006-2010 (Income and Poverty)

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Census Tracts 2010

    Date of Data: 2010

    Map Classification Scheme: The Population Overlays are symbolized using a thick gray boundary with a gray fill and are designed to be used as an overlay with other indicators to easily locate potential areas of interest.
     

    Data Table Field Headings: No attribute data are associated with these indicators.
     

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    Description of Other Relevant Demographic Indicators (not mapped)

    Persons with Disabilities

    Persons with disabilities -- defined by the United Nations as persons “who have long-term physical, mental, intellectual or sensory impairments which in interaction with various barriers may hinder their full and effective participation in society on an equal basis with others” -- are significantly impacted by a broad range of social and economic disparities. Addressing these disparities is essential in order to achieve broader regional equity. For this reason, mapping the population of persons with disabilities as a whole, as well as by specific types of disabilities, was a top priority for the Atlas project.  However, while the American Community Survey collects some basic data on disability, the sample sizes are too small to enable us to map these data in any meaningful way.

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    THEME: ECONOMIC OPPORTUNITY

     

    Other Relevant Indicators (not mapped)

    • Proximity to Living Wage Jobs Accessible to Low-Skilled Workers
    • Minority-Owned Businesses
    • Commuting and Job Location Patterns
    • Distribution of Public Investments
    • Factors Affecting Economic Development
    • Employment Rates

     

    Economic Opportunity: Transit Access to Family Wage Jobs

    • Transit Access to Family Wage Jobs (up to 60 minutes travel time)
    • Transit Access to Family Wage Jobs (up to 90 minutes travel time)

    Description: Transit access can be conceptualized as the answer to the question, "How many family-wage jobs do I have access to via transit (multimodal) within 60 or 90 minutes of travel time?" Family-wage jobs are defined by the Institute of Portland Metropolitan Studies as the income level needed to support one adult, one preschooler, and one school age child. The income level varies by the county of residence: Clark ($48,172), Clackamas ($54,343), Washington ($58,915), and Multnomah ($47,244).

    "Although few of us work in the same neighborhoods where we live, people who rely on public transportation may have real difficulty finding jobs that are accessible to poor, inner-city neighborhoods...[S]ome research has found evidence that distance from jobs reduces employment rates, particularly among lower-skilled adults" (Turner, Margery Austin, "Why Housing Mobility? The Research Evidence Today," January/February 2005 issue of Poverty and Race).

    Data Source: Portland Bureau of Planning & Sustainability (BPS) Analysis of Brookings Institute Data

    For further details on data processing protocols access the following link:

    [Family Wage Jobs]

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Raster (264' cell size)

    Date of Data: 2012

    Map Classification Scheme: These rasters are calculated based on a 1-5 scale. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Low: Cells with access 1 mile or greater.
    2 Medium Low: Cells with access 3/4 to 1 mile.
    3 Medium: Cells with access 1/2 to 3/4 mile.
    4 Medium High: Cells with access 1/4 to 1/2 mile.
    5 High: Cells with access 0 to 1/4 mile.

    Data Table Field Headings: Summary tables for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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    Economic Opportunity: Transportation to Jobs (2013 TAZs)

    Description: The Transportation to Jobs indicator represents the number of jobs that households in a given Transportation Analysis Zone (TAZ) perceive as being accessible. This determination of accessibility is based on an interim output of Metro's regional model that quantifies multimodal accessibility from a given TAZ to all others. The basic interpretation is this: if a TAZ shows up as "hot," that means that households in that TAZ have relatively good access to jobs.

    Transportation analysis zones are intended to capture relatively homogenous areas as far as land use and urban form, and therefore travel behavior, are concerned. The TAZ is the fundamental unit of geography in Metro’s transportation model, and household and employment data at the TAZ level are a primary model input.

    Data Source: Metro

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Transportation Analysis Zone (TAZ)

    Date of Data: 2013

    Map Classification Scheme: Five classes based on natural breaks.

    Class/Values Description
    1 Low Accessibility
    2 Medium-Low Accessibility
    3 Medium Accessibility
    4 Medium-High Accessibility
    5 High Accessibility

    Data Table Field Headings:

    Heading Description
    Transportation Analysis Zone (TAZ) TAZ ID
    jobs2005 Number of jobs estimated within the TAZ

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    Economic Opportunity: Locations of Workforce Training Sites and Employment-Related Services

    Description: The Locations of Workforce Training and Employment-Related Services indicator shows the locations of workforce training sites and other employment-related public services.

    Data Limitations: This is an incomplete list, compiled through readily available sources. It shows locations of training or service sites but does not indicate how many persons the site has serviced or the extent to which the site has met local needs for workforce training or employment-related services.

    Data Source: 211info Data; Oregon Worksource; Clark County Employment Services (WA)

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Points

    Date of Data: 2012

    Map Classification Scheme: Single Point Symbol

    Data Table Field Headings:

    Heading Description
    Name Name of Site
    Address Address of Site
    City City of Site
    State State of Site
    Zip Zip Code of Site

    Link to Data [Excel Spreadsheet]

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    Economic Opportunity: Adult Educational Attainment

    Description: The Adult Educational Attainment indicators show the level of education for the population 25 years and older. Standard U.S. Census categories are used.

    Data Source: American Community Survey (ACS 2006-2010 estimates); S1501 Educational Attainment

    Data Limitations: Because of sample size issues, the margin of error tends to be quite high when disaggregating ACS data. Consequently, the Educational Attainment indicators are mapped at the PUMA level -- a relatively coarse geographic unit but one where the margin of errors are at an acceptable level. The map can be used to discern general patterns only. The data table (downloadable below) contains information on the margin of error and should be consulted before using this data for any analyses.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: PUMA 2010

    Date of Data: ACS 5-Year Estimates (2006-2010)

    Map Classification Scheme: 9-12th Grade (no diploma)

    Class/Values Description
    2% to 5% Percent of Population 25 and Over with 9-12th Grade Education (no diploma).
    6% to 7% Percent of Population 25 and Over with 9-12th Grade Education (no diploma).
    8% to 10% Percent of Population 25 and Over with 9-12th Grade Education (no diploma).

    Data Table Field Headings: 9-12th Grade (no diploma)

    Heading Description
    PUMA PUMA ID
    P9_12 Percent of Population 25 and Over with 9-12th Grade Education (no diploma).
    P9_12MOE Percent of Population 25 and Over with 9-12th Grade Education (no diploma) Margin of Error.

    Map Classification Scheme: High School Diploma

    Class/Values Description
    10% to 21% Percent of Population 25 and Over with a High School Diploma.
    22% to 28% Percent of Population 25 and Over with a High School Diploma.
    29% to 33% Percent of Population 25 and Over with a High School Diploma.

    Data Table Field Headings: High School Diploma

    Heading Description
    PUMA PUMA ID
    PHSGrad Percent of Population 25 and Over with a High School Diploma.
    PHSMOE Percent of Population 25 and Over with a High School Diploma Margin of Error.

    Map Classification Scheme: Some College

    Class/Values Description
    19% to 22% Percent of Population 25 and Over with Some College.
    23% to 27% Percent of Population 25 and Over with Some College.
    28% to 30% Percent of Population 25 and Over with Some College.

    Data Table Field Headings: Some College

    Heading Description
    PUMA PUMA ID
    PSomeColl Percent of Population 25 and Over with Some College.
    PSCollMOE Percent of Population 25 and Over with Some College Margin of Error.

    Map Classification Scheme: BA-BS Degree

    Class/Values Description
    11% to 15% Percent of Population 25 and Over with a BA or BS Degree.
    16% to 22% Percent of Population 25 and Over with a BA or BS Degree.
    23% to 34% Percent of Population 25 and Over with a BA or BS Degree.

    Data Table Field Headings: BA-BS Degree

    Heading Description
    PUMA PUMA ID
    PBA Percent of Population 25 and Over with a BA or BS Degree.
    PBAMOE Percent of Population 25 and Over with a BA or BS Degree Margin of Error.

    Map Classification Scheme: Professional-Graduate Degree

    Class/Values Description
    5% to 8% Percent of Population 25 and Over with a Professional or Graduate Degree.
    9% to 15% Percent of Population 25 and Over with a Professional or Graduate Degree.
    16% to 28% Percent of Population 25 and Over with a Professional or Graduate Degree.

    Data Table Field Headings: Professional-Graduate Degree

    Heading Description
    PUMA PUMA ID
    PPRof Percent of Population 25 and Over with a Professional or Graduate Degree.
    PProfMOE Percent of Population 25 and Over with a Professional or Graduate Degree Margin of Error.

    Link to Data [Excel Spreadsheet]

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    Description of Other Relevant Economic Indicators (not mapped)

    Proximity to Living Wage Jobs Accessible to Low-Skilled Workers

    A key measure of economic opportunity is the availability of jobs that are accessible to workers with an associate’s degree or below and that pay a living wage. The lack of geographic proximity and/or transit access to living wage jobs that are accessible to workers with limited education limits those workers’ economic opportunities and contributes to unemployment and underemployment.  Mapping this data was a high priority for the Equity Atlas project, but data on employers, wages, and job types are not available at the necessary level of geographic specificity to enable us to map this information in a meaningful or accurate way.

    Minority Owned Businesses

    Business creation and small business growth are a reflection of one component of economic opportunity in a community. The demographic profile of business owners and how those demographics compare to the demographics of the community as a whole provide insights into whether the opportunities for business ownership are equitably distributed. The racial and ethnic composition of business ownership in a community also provides an indication of whether local businesses are likely to offer culturally appropriate goods and services to meet the needs of local residents. Summary-level data on minority owned businesses is available by county (see, for example, Greater Portland Pulse Business Loan Data) but data on the demographics of individual business owners is not available, which makes it impossible to map this information in a meaningful way.

    Commuting and Job Location Patterns

    In an equitable region, employment opportunities and affordable housing are distributed throughout the region, providing low-wage workers with geographic access to jobs and enabling workers to live within a reasonable commute of their jobs. Research suggests that the working poor spend a higher portion of their income on commuting than the general population, and their combined costs of commuting and housing make up a larger portion of their household budgets in relation to other households. To map this issue, we would need data showing where neighborhood residents work and where the employees of local employers live. However, for privacy reasons, data on the residential addresses of employees is not publicly available in a format that is mappable.

    Distribution of Public Investments

    Creating equitable access to the resources and opportunities necessary for health and well-being requires an intentional examination of current and past investment strategies and the prioritization of investments in infrastructure, the built environment, and public services in underserved communities to ensure that all people and communities can thrive. For this reason, an examination of the distribution of public investments is critical as part of a comprehensive analysis of regional equity issues. This includes not only the geographic distribution of public spending, but who is benefitting from the jobs and government contracts produced by those investments. Unfortunately, there is no way to meaningfully map this issue with the available data. Data on public investments is not available in a consistent and comprehensive way across jurisdictions, and there is limited data on the geographic distribution of those public investments by neighborhood. Data on government contracts is collected by many public agencies, but it is not available consistently across agencies in a way that can be meaningfully mapped.

    Factors Affecting Economic Development

    Various factors affect the potential for economic development and job creation in a given community. These include the presence or absence of regulations that can either promote or impede economic development as well as the availability of large tracts of land for commercial, residential, and industrial development. The Atlas mapping tool’s reference layers do include some data that are relevant to this issue, such as zoning codes and the locations of vacant land; these layers can be added to any map created within the tool. However, the data on vacant land does not distinguish between the potential uses of that land, which limits the value of that data for analyzing economic development opportunities. Similarly, comprehensive data that would enable us to map economic development regulations is not available, and gathering that data was beyond the scope of this project.

    Employment Rate

    The employment and unemployment rates in a community are a key indicator of economic opportunity, particularly when disaggregated by income and race. However, while employment data is available at a county level, it is not available at smaller geographic levels. To view unemployment data summarized by county for the metro region, see the Greater Portland Pulse webiste.
     

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    THEME: EDUCATION

     

    Other Relevant Indicators (not mapped)

    • Cultural Competency
    • Community Schools
    • Parent Involvement
    • Post-Secondary Enrollment
    • Affordability of Child Care

    Education: Proximity to Nearest Elementary School

    Description: The Proximity to Elementary Schools indicator shows the walking distance to elementary schools (based on the location of the school).

    Data Limitations: This indicator maps the walking distance to the nearest elementary school. However, the nearest elementary school may not necessarily be the assigned neighborhood school for each address. Furthermore, in some school districts, children may have the option of attending elementary schools outside their catchment areas, meaning that their "access" to education expands beyond their assigned neighborhood school. We chose to map proximity to elementary schools (as opposed to middle and high schools) because research shows that proximity to elementary schools is a strong determinant of school attendance even when school choice programs exist (Hastings, et al., 2006, "Parental Preferences and School Competition: Working Paper No. 11805; Hastings, Justine and Jeffrey Weinstein, 2008, "Information, School Choice, and Academic Achievement: Evidence from Two Experiments," Quarterly Journal of Economics 123(4)].

    Data Source: Metro RLIS (Places-Schools)

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2012

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to an elementary school. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from the school.
    2 Cells within 3/4 to 1 mile of the school.
    3 Cells within 1/2 to 3/4 mile of the school.
    4 Cells within 1/4 to 1/2 mile of the school.
    5 Cells within 1/4 mile of the school.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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    Education: Proximity to Headstart and Licensed Childcare Centers

    Description: The Proximity to Headstart and Childcare Centers indicator shows relative distance to facilities, programs and centers that serve pre-school and young children.

    Data Source: Oregon Department of Education (OR Headstart); State of Oregon, Employment Department, Child Care Division (OR Childcare); Washington State Association of Head Start and the Early Childhood Education and Assistance Program (WA Headstart); Washington State Department of Early Learning (WA Childcare)

    Data Limitations: The data for this indicator only capture childcare centers that are licensed. As a result, it does not include some private preschools that are not required to be licensed. It is also important to note that affordability and the availability of open slots tend to be greater barriers to childcare access than geographic proximity. Unfortunately, comprehensive data is not available in a format that would enable mapping of these factors.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2012

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using distance to a point (Headstart locations and Childcare Centers). Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from the school.
    2 Cells within 3/4 to 1 mile of the school.
    3 Cells within 1/2 to 3/4 mile of the school.
    4 Cells within 1/4 to 1/2 mile of the school.
    5 Cells within 1/4 mile of the school.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and type of the early childhood education and care centers.

    Link to Data [Excel Spreadsheet]

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    Education: Percent of Students Eligible for Free or Reduced Cost Lunch

    Description: The Students Eligible for Free or Reduced Cost Lunch indicator shows the percentage of K-12 students taking part in the free and reduced cost lunch program. This indicator is often used as a proxy for childhood poverty.

    Data Source: OR Department of Education (ODE); WA Office of the Superintendent of Public Instruction (WAOSPI)

    Geographic Unit: Graduated Points (by school)

    Date of Data: 2011-12 Academic Year

    Map Classification Scheme: Four classes based on natural breaks.
     

    Class/Values Description
    2% to 30% Percent of students participating in the free or reduced cost lunch program.
    31% to 45% Percent of students participating in the free or reduced cost lunch program.
    46% to 70% Percent of students participating in the free or reduced cost lunch program.
    71% to 95% Percent of students participating in the free or reduced cost lunch program.

    Data Table Field Headings:

    Heading Description
    NAME Name of School
    LEVEL

    Grade Level of School

    • Elementary
    • Middle or Junior High
    • High School
    • Various Grade Levels
    • Skill Center or Alternative
    • Special
    FREELUNCHP Percent of Students Participating in the Free or Reduced Cost Lunch Program

    Link to Data [Excel Spreadsheet]

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    Education: General School Data

    Description: The General School Data indicators compile various information consistently tracked each academic year on all schools.

    Data Limitations: Average class size is reported for elementary schools only (where students generally remain with the same teacher for the entire school day); the 3rd grade reading benchmark was selected as a critical indicator of student learning and success (test results for other benchmarks and grades are available on the ODE and WAOSPI websites); percent minority students is an aggregate of all minority categories tracked by schools. Data is provided for all public and schools with special status (charter and alternative schools). Generally, private schools are not included.

    The Schools Data indicators that were selected were limited by the available data. These indicators provide some indication of the educational quality at a given school, but they also are limited by the following factors:

    Average Teacher Experience (years): This indicator is intended to provide a measure of teacher quality. Levels of teacher experience do tend to correlate with teaching quality, but this does not necessarily mean that more years of experience always translates into better teaching quality. Research suggests that other indicators such as access to teacher mentorship programs may be better measures of teacher performance; unfortunately comprehensive data on those indicators are not currently available.

    Schools Meeting/Not Meeting Adequate Yearly Progress (AYP): AYP is the measure by which schools are held accountable for student performance under the No Child Left Behind Act of 2011. Many critiques have been made of the AYP model, but AYP data is the only student performance data currently available in a consistent format across schools, which is why this data is included in the Atlas. While the data provide some useful information, any interpretation of the data should be informed by the following caveats: (1) The standardized tests that are the basis for the AYP assessment have been criticized for various reasons including cultural bias and providing an insufficient measure of student learning; (2) Test scores are as much a reflection of the socioeconomic status of the students in a school as they are of teaching quality; (3) The AYP model itself has been criticized as flawed.

    Schools Meeting State Benchmarks for 3rd Grade Reading: This measure relies on standardized testing, which is subject to the same limitations described above..

    Data Source: Oregon Department of Education; Washington Office of the Superintendent of Public Instruction

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Points

    Date of Data: 2011-12 Academic Year

    Map Classification Scheme: Percent Minority Students (K-12)

    Note: "Minority" is an aggregated category from students who identified as Hispanic, African-American, Asian, Native American, Other, and more than one race. Class breaks are determined through natural breaks in the range of values.

    Class/Values Description
    5% to 25% Percent of total student body identifying as a minority (race or ethnicity).
    25% to 42% Percent of total student body identifying as a minority (race or ethnicity).
    43% to 64% Percent of total student body identifying as a minority (race or ethnicity).
    65% to 100% Percent of total student body identifying as a minority (race or ethnicity).

    Data Table Field Headings: Percent Minority Students (K-12)

    Heading Description
    NAME Name of School
    LEVEL Grade Level of School
    SCHLSTUDC Student Count
    SCHLWHITEP Student White Percent
    SCHLBLACKP Student African American Percent
    SCHLHISPP Student Hispanic Percent
    SCHLASIANP Student Asian Percent
    SCHLAMINDP Student Native American Percent
    SCHLUNKPC Student Other Race Percent
    SCHLMULTIP Student Multiple Races Percent
    SCHLMNRTYP Aggregate Student All Race/Ethnicity Percent

    Map Classification Scheme: Schools Meeting/Not Meeting Adequate Yearly Progress (AYP)

    Class/Values Description
    Not Met Schools that did not demonstrate Annual Yearly Progress as required by the No Child Left Behind regulations.
    Met Schools that succeeded in demonstrating Annual Yearly Progress as required by the No Child Left Behind regulations.

    Data Table Field Headings: Schools Meeting/Not Meeting Adequate Yearly Progress (AYP)

    Heading Description
    NAME Name of School
    LEVEL Grade Levels of School
    AYP Demonstration of Annual Yearly Progress (Met or Not Met)

    Map Classification Scheme: Percent Schools Meeting State Benchmarks for 3rd Grade Reading

    Class/Values Description
    8% to 60% Percent of students meeting 3rd grade reading benchmarks.
    61% to 76% Percent of students meeting 3rd grade reading benchmarks.
    77% to 87% Percent of students meeting 3rd grade reading benchmarks.
    88% to 97% Percent of students meeting 3rd grade reading benchmarks.

    Data Table Field Headings: Percent Schools Meeting State Benchmarks for 3rd Grade Reading

    Note: 9999 indicates no data (all middle and high schools will have this value)).

    Heading Description
    NAME Name of school.
    LEVEL Grade levels of school.
    per_read Percent students passed state benchmarks in 3rd grade reading (elementary only).

    Map Classification Scheme: Average Class Size (Elementary)

    Class/Values Description
    Under 20 Average class size for the elementary school is under 20 students.
    20 to 22 Average class size for the elementary school is between 20 and 22 students.
    23 to 25 Average class size for the elementary school is between 23 and 25 students.
    Over 25 Average class size for the elementary school is over 20 students.

    Data Table Field Headings: Average Class Size (Elementary)

    Note: 9999 indicates no data.

    Heading Description
    NAME Name of School
    LEVEL Grade Levels of School (Elementary Only)
    ELEMCLSZ Average Class Size (Elementary Schools Only)

     

    Map Classification Scheme: Percent Graduation Rate

    Class/Values Description
    < 55% Percent of students graduating with diploma by high school cohort.
    55% to 70% Percent of students graduating with diploma by high school cohort.
    71% to 85% Percent of students graduating with diploma by high school cohort.
    > 85% Percent of students graduating with diploma by high school cohort.

    Data Table Field Headings: Percent Graduation Rate

    Note: 8888 indicates elementary or middle schools (not applicable); 9999 indicates no data.

    Heading Description
    NAME Name of School
    LEVEL Grade Levels of the School
    PGRADRATE Graduation Rate per High School Cohort (percent)

    Map Classification Scheme: Average Teacher Experience (years)

    Class/Values Description
    <= 7 years Average teacher experience for the school is less than or equal to 7 years.
    7.1 to 14 years Average teacher experience for the school is between 7.1 and 14 years.
    > 14 years Average teacher experience for the school is greater than 14 years.

    Data Table Field Headings: Average Teacher Experience (years)

    Heading Description
    NAME Name of School
    LEVEL Grade Level of School
    TEACHEXP Average Teacher Experience per school (in years)

    Link to Data [Excel Spreadsheet]

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    Education: Number of Languages Spoken by Students [OR schools only]

    Description: The Languages Spoken indicator represents the total number of languages spoken by the student body in each school (for Oregon schools only). The map is an aggregate of all the languages represented within a particular school. The link to the Excel spreadsheet below breaks out the specific languages for each school. 156 languages are represented in the dataset.

    Data Source: Oregon Department of Education

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon)

    Geographic Unit: Points

    Date of Data: 2010-11 Academic Year

    Map Classification Scheme:

    Class/Values Description
    1 to 8 Number of different languages spoken by student body in a school.
    9 to 16 Number of different languages spoken by student body in a school.
    17 to 26 Number of different languages spoken by student body in a school.
    27 to 50 Number of different languages spoken by student body in a school.

    Data Table Field Headings:

    Heading Description
    NAME Name of School
    LEVEL Grade Levels of School
    LANGUAGES Number of Languages Spoken by Student Body

    Link to Data [Excel Spreadsheet]

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    Education: Availability of AP-IB Classes (High School) and Arts-Media Classes [OR schools only]

    Description: The AP-IB (Advanced Placement and International Baccalaureate) and Arts-Media Classes indicators show the number of these types of courses offered by each school (for Oregon schools only).

    Data Limitations: These indicators are intended to reflect the range of course options available to students. However, they do not measure student access to these courses. Enrollment data would provide a better indication of student access to these course options, but that data is not available in a comprehensive format across schools.

    Data Source: Oregon Department of Education

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon)

    Geographic Unit: Points

    Date of Data: 2011-12 Academic Year

    Map Classification Scheme: Number of AP-IB Classes (High School)

    Class/Values Description
    0 Number of AP and IB classes offered at the school.
    1 to 5 Number of AP and IB classes offered at the school.

    Data Table Field Headings: Number of AP-IB Classes (High School)

    Note: 8888 indicates elementary and middle schools (not applicable); 9999 indicates no data reported.

    Heading Description
    NAME Name of school.
    LEVEL Grade levels of school.
    AP_IB Number of Advanced Placement and International Baccalaureate Courses offered at the school (high schools only).

    Map Classification Scheme: Number of Arts-Media Classes Offered

    Class/Values Description
    0 Number of arts, drama, and media classes offered at the school.
    1 - 30 Number of arts, drama, and media classes offered at the school.
    31 - 60 Number of arts, drama, and media classes offered at the school.
    61 - 90 Number of arts, drama, and media classes offered at the school.
    90 - 154 Number of arts, drama, and media classes offered at the school.

    Data Table Field Headings: Number of Arts-Media Classes Offered

    Note: 9999 indicates no data reported.

    Heading Description
    NAME Name of school.
    LEVEL Grade levels of school.
    ARTS Number of arts, drama, media courses offered at the school.

    Link to Data [Excel Spreadsheet]

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    Description of Other Relevant Education Indicators (not mapped)

    Cultural Competency

    Given the racial, ethnic, and socio-economic diversity of our region’s public schools, it is imperative that teachers have the cultural competency to be able to connect with, respond to, and interact effectively with all students regardless of their backgrounds. Culturally competent teachers contextualize and integrate classroom learning with students’ everyday experiences, beliefs, values, and cultural norms. The cultural competency of teachers is a critical factor in closing the achievement gap. However, no data is available to enable us to measure and map the levels of cultural competency of teachers within our region’s public schools.  Cultural competency in general is too complex an issue to measure quantitatively or to map. Data on teacher diversity or on teacher training in cultural competency – both of which can serve as reasonable proxies -- is not available in a comprehensive way across schools.

    Community Schools

    “Community schools” use public school buildings to provide a broad range of programs and activities for children and the broader community after school hours.  Programs like Multnomah County’s Schools Uniting Neighborhoods (SUN) turn schools into community hubs and provide a convenient way for community members to access services and programs.  Access to schools after hours can also increase opportunities for physical activity in communities that are lacking parks, sidewalks and safe places for physical activity. Many schools across the region operate as community schools, and mapping those schools would have been a valuable addition to the Atlas. But data on community schools is not available in a consistent manner across the metro area’s school districts.

    Parent Involvement

    An individual school’s ability to offer enhanced educational opportunities to students is often affected by school fundraising levels and the availability of parent volunteers. This situation can create inequities because levels of fundraising tend to be higher in schools with more affluent parents, and parents who must work multiple jobs to make ends meet are less available to volunteer in the classroom. While parent involvement can have a significant impact on the quality of the education available at a given school, comprehensive data is not available to enable us to map parent involvement by school. Some data is available on school fundraising, but it is not available in a format that can be consistently and accurately compared across schools region-wide. Similarly, some data is available on the presence of Parent Teacher Associations in schools, but this information is not available in a consistent way across schools and is not an effective proxy for overall parent involvement levels.

    Post-Secondary Enrollment

    Enrollment in post-secondary education following high school graduation is correlated with higher employment rates and greater income earning potential.  According to the Multnomah County Cradle to Career initiative, “Current economic forecasts indicate a need for increased numbers of students achieving success in postsecondary education. Not only must we increase the total number of students who enroll in postsecondary programs but we must actively recruit and retain students of color if they are to be successful. All students require academic and personal support to make a successful transition from high school to complete a degree and join the workforce prepared for a career.”  Some county-level summary data is available for this indicator (see, for example Cradle to Career) but data was not available to enable us to map post-secondary enrollment rates by school.

    Affordability of Child Care

    Childcare affordability is a significant issue for all working parents, particularly parents with low incomes. The lack of affordable childcare can create barriers to employment and can force parents to place their children in unsafe situations. The inability to afford childcare can also limit a family’s access to quality early childhood education, which can have lasting effects on a child’s educational success. While childcare affordability is a fundamental equity issue, data is not available to permit us to map this issue.

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    THEME: FOOD

     

    Other Relevant Indicators (not mapped)

    • Affordable Food
    • Culturally Appropriate Food
    • Healthful Food

     


    Food: Proximity to Supermarkets and Grocery Stores

    Description: The Supermarkets and Grocery Store indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes supermarkets and other grocery stores (445110).

    Data Limitations:  The classification of stores as supermarkets and grocery stores by NAICS codes is based on self-reported information; consequently, some stores which do not meet the common sense definition of a supermarket or grocery stores may be included in the data.

    It is important to note that proximity to supermarkets and grocery stores is only one component of food access. Comprehensive data is not available to enable us to map other factors affecting food access, such as affordability, healthfulness, or cultural appropriateness of the food available at a given store, but these factors are key components of a community’s access to food.

    Data Source: ESRI Business Analyst

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2010

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using distance to a point. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from the point.
    2 Cells within 3/4 to 1 mile of the point.
    3 Cells within 1/2 to 3/4 mile of the point.
    4 Cells within 1/4 to 1/2 mile of the point.
    5 Cells within 1/4 mile of the point.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet that includes name, address, city, state, zip and NAICS codes of the selected businesses.

    Link to Data [Excel Spreadsheet]

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    Food: Proximity to Farmers' Markets and Produce Stands

    Description: The Farmers' Market indicator provides information on access to fresh foods and was manually compiled from the national list maintained by the U.S. Department of Agriculture and other sources including Portland Farmers' Markets and the Oregon Environmental Council. The list of farmers' markets was combined with produce stands retrieved from a list of NAICS codes (North American Industry Classification System) that includes fruit and vegetable markets (permanent) (445230).

    Data Source: U.S. Department of Agriculture; Portland Farmers' Market; Oregon Environmental Council; ESRI Business Analyst

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2012 (primary data collection); 2010 (Business Analyst)

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using distance to a point. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from the point.
    2 Cells within 3/4 to 1 mile of the point.
    3 Cells within 1/2 to 3/4 mile of the point.
    4 Cells within 1/4 to 1/2 mile of the point.
    5 Cells within 1/4 mile of the point.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet that includes name, address, city, state, and zipcode of the selected businesses and organizations.

    Link to Data [Excel Spreadsheet]

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    Food: Proximity to Typical Sources of "Unhealthy Food" (liquor stores, convenience stores, fast food restaurants)

    Description: The Unhealthy Food indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes Fast-Food Restaurants (722211), Convenience Stores (445120), Beer, Wine, and Liquor Stores (445310), and Gasoline Stations with Convenience Stores (447110).

    Data Limitations: This indicator is based on research showing that proximity to sources of unhealthy food can have a negative impact on health.

    Access to Affordable and Nutritious Food: Report to Congress

    The Grocery Gap (PolicyLink)

    While fast food restaurants, convenience stores, and liquor stores are typically sources of unhealthy food and drink options, the data for this indicator is limited to NAICS classification codes which don't distinguish between the "typical" convenience store or fast food restaurant and those that offer more healthy options.

    Data Source: ESRI Business Analyst

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2010

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using distance to a point. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from the point.
    2 Cells within 3/4 to 1 mile of the point.
    3 Cells within 1/2 to 3/4 mile of the point.
    4 Cells within 1/4 to 1/2 mile of the point.
    5 Cells within 1/4 mile of the point.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet that includes name, address, city, state, zip and NAICS codes of the selected businesses.

    Link to Data [Excel Spreadsheet]

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    Food: Proximity to Supplemental Food Programs (food pantries and summer food sites)

    Description: The Supplemental Food Programs indicator includes sites that provide access to supplemental food (food pantries) and summer food programs for children.

    Data Source: 211info Data (food pantries); Metro School Districts and Web Research (summer food programs)

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2012

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using distance to a point. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from the point.
    2 Cells within 3/4 to 1 mile of the point.
    3 Cells within 1/2 to 3/4 mile of the point.
    4 Cells within 1/4 to 1/2 mile of the point.
    5 Cells within 1/4 mile of the point.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet that includes name, address, city, state, zip of the site and a code that indicates annual hours of operation.

    Link to Data [Excel Spreadsheet]

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    Food: Proximity to Food Stores and Farmers' Markets Accepting WIC and/or SNAP (OR Only)

    Description: The Food Stores and Farmers' Markets that Accept WIC and SNAP indicator provides information about public access to food stores and fresh food participating in federal food programs.

    NOTE: The datasets are separated into those accepting WIC and those accepting SNAP in order to prevent duplicate features (most grocery stores that accept SNAP also accept WIC).

    Data Limitations: The datasets includes sites for Oregon only (with a few farmer's markets noted in Clark County).

    Data Source: US Department of Agriculture Nutrition Program

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2012

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using distance to a point. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from the point.
    2 Cells within 3/4 to 1 mile of the point.
    3 Cells within 1/2 to 3/4 mile of the point.
    4 Cells within 1/4 to 1/2 mile of the point.
    5 Cells within 1/4 mile of the point.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet that includes name, address, city, state, zipcode of the selected businesses and organizations.

    Link to Data [Excel Spreadsheet]

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    Food: Locations of Community Gardens

    Description: The Community Gardens indicator shows the location of community gardens in the Portland-Vancouver metropolitan area. These are locations only. No data is provided on number of garden plots or other information about the site (e.g. waiting lists, etc.).

    Data Limitations: Many community gardens have limited capacity and extensive waiting lists. This indicator simply shows the locations of the community gardens, but does not reflect the availability of community garden plots.

    The following link is a map of Portland Community Gardens (2012) that shows existing gardens and planned gardens:

    [Portland Community Gardens]

    Data Source: Primary research through the web, contacting local organizations and neighborhood associations.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon); Clark County (Washington)

    Geographic Unit: Points

    Date of Data: 2012

    Map Classification Scheme: The map features are displayed using a single symbol.

    Data Table Field Headings:

    Heading Description
    Garden_Nam Name of community garden.
    Street_Add Street address of community garden.
    City_1 City of community garden.
    Zip_Code Zipcode of community garden.

    Link to Data [Excel Spreadsheet]

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    Description of Other Relevant Food Indicators (not mapped)

    Affordable Food

    The Atlas depicts the locations of supermarkets, grocery stores, farmers markets, and produce stands. But geographic proximity to food retailers is just one component of access. For many households, the availability of affordable food is a far more relevant measure of access. Unfortunately, there is no available data that would enable us to effectively map food affordability at a regional scale. Gathering this data would require conducting a market basket survey at every food retailer in the region and this data would need to be updated on a regular basis. A pilot project of such an effort led to the conclusion that collecting the data at a regional scale was beyond the capacity of this project.

    Culturally Appropriate Food

    A comprehensive analysis of food access should also take into account the availability of culturally appropriate food.  Geographic proximity to food retailers is irrelevant if those retailers do not carry the specific foods that a household needs in order to feed itself.  Unfortunately, as with affordable food, there is no data that would enable us to map the availability of culturally appropriate food at a regional scale. Gathering that data may be possible through a market basket survey tool, but this would be an extremely complex undertaking because the survey tool would need to be tailored to assess the availability of foods that are culturally appropriate for the specific populations that live within close proximity to each food retailer.

    Healthful Food

    The availability and affordability of healthful food is another important component of food access. By mapping the locations of grocery stores, supermarkets, farmers’ markets, and produce stands, the Atlas provides some information on the likely locations of healthful food, but this information is limited. We can assume that all of these retailers carry at least some fresh produce and other healthful foods, but the Atlas does not provide any information about the relative quality, quantity, or price of healthful foods at these retail locations, and it does not take into account other potential sources of healthful food, such as convenience stores that offer fresh produce.  Unfortunately, as with the other indicators in this section, gathering this data would require conducting a market basket survey at every food retailer in the region and this data would need to be updated on a regular basis.

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    THEME: HEALTH CARE

     

    Other Relevant Indicators (not mapped)

    • Health Insurance
    • Availability of Affordable Mental Health Care, Dental Care, and Alcohol and Drug Treatment
    • Availability of Culturally Appropriate Health Care

    Health Care: Proximity to Primary Care Facilities

    Description: The Proximity to Primary Care Facilities indicator shows distance to primary medical care facilities including family/general medicine, pediatrics and obstetrics.

    Data Limitations: Distance is only one element of access to medical care facilities. While the map gives some indication of the location and relative density of these facilities, access to medical care is determined only in part by geographic proximity. Affordability, insurance access, cultural competency, and provider capacity are also important factors. And for individuals with health insurance, other factors, such as insurance provider networks, also dictate access to medical providers. Unfortunately, none of these other factors could be mapped for this project due to lack of relevant spatial data.

    Data Source: Oregon Health Authority (OR); ESRI Business Analyst (WA)

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: Proximity Raster (264' cell size)

    Date of Data: 2012 (OR); 2010 (WA)

    Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

    Rank
    Description
    1 Cells greater than 1 mile from a street.
    2 Cells within 3/4 to 1 mile of a street.
    3 Cells within 1/2 to 3/4 mile of a street.
    4 Cells within 1/4 to 1/2 mile of a street.
    5 Cells within 1/4 mile of a street.

    Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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    Health Care: Health Care Providers that Accept Medicaid and/or Medicare

    • Health care providers that accept Medicaid (includes OHP -- Oregon Health Plan)
    • Health care providers that accept Medicare

    Description: The Health Care Providers that Accept Medicaid and/or Medicare indicators show the number of medical practitioners that accept OHP/Medicaid and Medicare patients aggregated by zipcode.

    Data Limitations: The data for this indicator is based on the National Provider Identifier database, which is a listing of all practitioners that have agreed to accept Medicaid and/or Medicare patients. Several practitioners may be associated with a single clinic or hospital, but each practitioner is counted separately in the database, which means that densities are likely to be greater for medical facilities with multiple practitioners who accept Medicaid and/or Medicare.

    Note: In some cases, the provider address listed in the National Provider Identifier database may reflect the home address of the provider rather than the provider's medical facility address. The database does not provide sufficient information that would make it possible to identify these cases. This could skew the data for any providers who live in a zipcode different from their medical facility zipcode.

    Data Source: Center for Medicare & Medicaid Services, National Provider Identifier Database

    The National Provider Identifier database is a list of all certified medical professionals that accept Medicare and Medicaid.

    Since most practitioners that accept Medicaid also accept Medicare patients, these two indicators are mapped separately in order to prevent an overcount (resulting from duplicate records). The configuration and large size of the database was not conducive to identifying and separating practitioners by whether they accept Medicaid, Medicare or both.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: Zipcode

    Date of Data: 2007

    Map Classification Scheme: Medicaid

    Class/Values
    Description
    0 Number of practitioners within the zipcode unit.
    1 - 63 Number of practitioners within the zipcode unit.
    64 - 128 Number of practitioners within the zipcode unit.
    129 - 236 Number of practitioners within the zipcode unit.
    237 - 1001 Number of practitioners within the zipcode unit.

    Map Classification Scheme: Medicare

    Class/Values
    Description
    0 Number of practitioners within the zipcode unit.
    1 - 125 Number of practitioners within the zipcode unit.
    126 - 244 Number of practitioners within the zipcode unit.
    245 - 367 Number of practitioners within the zipcode unit.
    368 - 1342 Number of practitioners within the zipcode unit.

    Data Table Field Headings: Medicaid and Medicare

    Heading Description
    ZIPCODE Zipcode number.
    OHP Number of providers that accept OHP and Medicaid patients.
    Medicare Number of providers that accept Medicare patients.
    Total_1 Total number of providers for both Medicaid and Medicare.

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    Health Care: Locations of Community, Public, and School-Based Health Clinics for Uninsured or Low-Income Patients

    Description: The Community, Public, and School-Based Health Clinics indicator provides information about the location and relative density of community, public, and school-based health clinics that accept uninsured or low-income patients.

    Data Limitations: The map may not include all clinics that accept uninsured or low-income patients, but is based on data available through the 211info database and Oregon Health Authority.

    Geographic proximity to a clinic does not necessarily translate into access to free or reduced cost medical care. The capacity of the health clinics varies, and some may not be able to accommodate new patients. The points on the map give a partial indication of clinic capacity based on the numbers of hours each clinic operates per year.

    Data Source: 211info Database (community and public health clinics) and Oregon Health Authority (school-based health clinics). 

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon)

    Geographic Unit: Graduated Points

    Date of Data: 2012 (community and public health clinics) and 2014 (school-based health clinics). 

    Map Classification Scheme: Graduated point symbols

    Class/Values
    Description
    1 Annual hours of operation unknown
    2 156 - 416 Hours (annual)
    3 468 - 1248 Hours (annual)
    4 2236 - 2496 Hours (annual)
    5 2600 - 3302 Hours (annual)

    Data Table Field Headings:

    Heading Description
    NAME The name of the clinic.
    ADDRESS The address of the clinic.
    CITY The city of the clinic.
    ZIP Zip code of the clinic.
    Label Average annual hours of operation.

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    Health Care: Rate of First Trimester Pre-natal Care

    Description: The First-Trimester Pre-natal Care indicator reflects maternal health care. Data are collected from a variety of sources as part of the public health surveillance system. The rate of women receiving first trimester pre-natal care includes all women receiving such care through licensed practitioners. Individual data has been aggregated to the 2000 census tract level based on residence information indicated in health records.

    Data Source: Oregon Health Authority and Washington Department of Health (Vital Statistics Records)

    Data Limitations: These data measure whether pre-natal care was initiated during the first trimester. While this is an important component of adequate prenatal care, it does not capture other key components such as the frequency of care, total number of visits, quality of care, and whether care continued past the first trimester.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: 2000 Census Tracts

    Date of Data: 2006-2010

    Map Classification Scheme:

    Class/Values
    Description
    57.42 - 68.72% Women that received first-trimester prenatal care within the measurement period.
    68.72 - 76.28% Women that received first-trimester prenatal care within the measurement period.
    76.29 - 83.46% Women that received first-trimester prenatal care within the measurement period.
    83.47 - 98.57% Women that received first-trimester prenatal care within the measurement period.

    Data Table Field Headings:

    Heading Description
    FIPS ID for the census tract.
    PNC_Year Measurement year.
    PNC_BRTHRS Care period (first trimester prenatal care).
    PNC_Count Raw count of mothers who received first-trimester prenatal care during the measurement period.
    PNC_POP Total count of patients.
    PNC_PCT

    Percent of mothers who received first-trimester prenatal care during the measurement period.

    999 indicates data that was not available or removed for confidentiality reasons.

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    Health Care: Rate of Well-Child Visits, 3-6 Years

    • Rate of Well-Child Visits, 3-6 years (by census tract)
    • Rate of Well-Child Visits, 3-6 years (by neighborhood)

    Description: The Well-Child Visits (3-6 years) indicator shows the percentage of children 3-6 years of age who received one or more well-child visits with a primary care provider during the measurement year.

    Data Source: Data are compiled from insurer claims data submitted to Oregon Health Care Quality Corporation. The data include administrative claims (billing) data from seven commercial health plans, two Medicaid managed care plans and the Oregon Health Authority Division of Medical Assistance Programs (Medicaid).

    Data Limitations: Data is reported only for those patients that were continuously enrolled in a health plan that participates in the Oregon Health Care Quality Corporation’s measurement and reporting initiative or Medicaid fee-for-service during the measurement year, with no more than one gap of up to 45 days. Data does not include uninsured patients, patients who pay for their own health care services, Medicare fee-for-service patients, or patients served by a plan or Medicaid provider that does not supply data to Quality Corp. The data, therefore, do not represent all persons living within a census tract or neighborhood.

    Data on well-child visits were geocoded by patient address. However, in order to maintain confidentiality, data were aggregated into either census tracts or neighborhoods. If the number of records failed to meet a minimum sample size threshold the data were not reported (indicated by a 999 in the attribute table). The sample size threshold that was used was based on the recommendations outlined by the CDC in their National Center for Health Statistics Staff Manual on Confidentiality. Based on this threshold, data from geographies where the numerator was less than 5 people, or the difference between the denominator and numerator was less than 5 people, were suppressed. As an example, if a geography had 50 patients in the denominator then it was reportable so long as the numerator was between 5 – 45. Additionally a denominator threshold of 25 was applied to ensure robust reported rates.

    Some patient records did not have complete patient street addresses. If the street address could not be accurately located within the aggregated geography, those patient records were not mapped.

    Clark County Data: Although the data for this indicator include information for some Clark County census tracts and neighborhoods, these data are less reliable than the data for Multnomah, Clackamas, and Washington counties and should be used with caution. The focus of Oregon Health Care Quality Corporation's work is in Oregon. Some of the participating health plans submit claims data for members living in Clark County, but many do not. For this reason the Clark County results are based on a narrow population of Clark County residents, and the health care/outcome results may not be representative of the larger population.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: 2010 Census Tracts and Neighborhoods

    Date of Data: Measurement Year 1/1/2011 - 12/31/2011

    Map Classification Scheme: Well-Child Visits, 3-6 years (by census tract or neighborhood)

    Class/Values
    Description
    0 - 52.7% The percentage of eligible members 3-6 years of age who received one or more well-child visits with a primary care provider during the measurement year.
    52.8 - 64.7% The percentage of eligible members 3-6 years of age who received one or more well-child visits with a primary care provider during the measurement year.
    64.8 - 72.7% The percentage of eligible members 3-6 years of age who received one or more well-child visits with a primary care provider during the measurement year.
    72.8 - 88.9% The percentage of eligible members 3-6 years of age who received one or more well-child visits with a primary care provider during the measurement year.
    Data Not Available

    Those geographic units that were removed due to data that did not meet the confidentiality threshold.

    Data Table Field Headings: Well-Child Visits, 3-6 years (by census tract or neighborhood)

    Heading Description
    ID FIPS code for the census tract or Neighborhood Name
    p_WellChild

    Percent of eligible members 3-6 years of age who received one or more well-child visits with a primary care provider during the measurement year.

    999 indicates data that was removed for confidentiality reasons.

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    Health Care: Rate of Potentially Avoidable Emergency Department Visits by Adults

    Description: The Potentially Avoidable Emergency Department Visits by Adults indicator shows the percentage of Emergency Department visits by adults that were for problems that could have been more appropriately managed by a primary care provider in an office or clinic setting. The measure is based on the primary diagnosis appearing on the MediCal list of preventable ICD-9 diagnosis codes. The data include only patients 18 years or older at the time of the emergency department visit.

    Data Source: Data are compiled from insurer claims data submitted to Oregon Health Care Quality Corporation. The data include administrative claims (billing) data from seven commercial health plans, two Medicaid managed care plans and the Oregon Health Authority Division of Medical Assistance Programs (Medicaid).

    Data Limitations: Data is reported only for Emergency Department visits by patients that were enrolled in a health plan that participates in the Oregon Health Care Quality Corporation’s measurement and reporting initiative or Medicaid fee-for-service on the data of the Emergency Department visit. Data does not include visits for uninsured patients, patients who pay for their own health care services, Medicare fee-for-service patients, or patients served by a plan or Medicaid provider that does not supply data to Quality Corp. The data, therefore, do not represent all Emergency Department visits for persons living within a census tract or neighborhood.

    Data on potentially preventable Emergency Department visits were geocoded by patient addresses. However, in order to maintain confidentiality, the data were aggregated into either census tracts or neighborhoods. If the number of records failed to meet a minimum sample size threshold the data were not reported (indicated by a 999 in the attribute table). The sample size threshold that was used was based on the recommendations outlined by the CDC in their National Center for Health Statistics Staff Manual on Confidentiality. Based on this threshold, data from  geographies where the numerator was less than 5 Emergency Department visits, or the difference between the denominator and numerator was less than 5 visits, were suppressed. As an example, if a geography had 50 Emergency Department visits in the denominator then it was reportable so long as the numerator was between 5 – 45. Additionally a denominator threshold of 25 was applied to ensure robust reported rates.

    Data were also analyzed for the rates of potentially preventable Emergency Department visits for children as well. However, a large percentage of census tracts and neighborhoods did not meet the specified confidentiality threshold. Because the resulting maps contained relatively few populated geographic units, these indicators were not included in the mapping tool.

    Some patient records did not have complete patient street addresses. If the street address could not be accurately located within the aggregated geography, those patient records were not mapped.

    Clark County Data: Although the data for this indicator include information for some Clark County census tracts and neighborhoods, these data are less reliable than the data for Multnomah, Clackamas, and Washington counties and should be used with caution. The focus of Oregon Health Care Quality Corporation's work is in Oregon. Some of the participating health plans submit claims data for members living in Clark County, but many do not. For this reason the Clark County results are based on a narrow population of Clark County residents, and the health care/outcome results may not be representative of the larger population.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: 2010 Census Tracts and Neighborhoods

    Date of Data: Measurement Year 1/1/2011 - 12/31/2011

    Map Classification Scheme: Rate of Potentially Avoidable Emergency Department Visists by Adults (by census tract or neighborhood)

    Class/Values
    Description
    0 - 9.3% The percentage of emergency room visits for potentially preventable problems during the measurement year.
    9.4 - 12.8% The percentage of emergency room visits for potentially preventable problems during the measurement year.
    12.9 - 19.4% The percentage of emergency room visits for potentially preventable problems during the measurement year.
    19.5 - 29.3% The percentage of emergency room visits for potentially preventable problems during the measurement year.
    Data Not Available Those geographic units that were removed due to data that did not meet the confidentiality threshold.

    Data Table Field Headings: Rate of Potentially Avoidable Emergency Department Visits by Adults (by census tract or neighborhood)

    Heading Description
    ID FIPS code for the census tract or Neighborhood Name
    p_EDVisits

    The percentage of emergency room visits for potentially preventable problems during the measurement year.

    999 indicates data that was removed for confidentiality reasons.

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    Description of Other Relevant Health Care Indicators (not mapped)

    Health Insurance

    Access to health insurance is a key determinant of access to health care. Unfortunately, data on health insurance rates is not available at a level of geographic granularity that would enable us to map it. (For data on insurance rates for the region as a whole, see Greater Portland Pulse Health Insurance Webpage.) As a proxy, we sought data for other related indicators such as the rate of emergency room use by uninsured patients, mapped by patient address. However, that data was also not available.

    Availability of Affordable Mental Health Care, Dental Care, and Alcohol and Drug Treatment

    Access to affordable mental health care, dental care, and alcohol and drug treatment is critical to support the overall health, stability, and employability of our region’s low-income and uninsured residents. The need for these services far outstrips their availability. Mapping the locations of the available services could help to inform planning and resource allocation to fill the gaps. However, we were unable to secure reliable, comprehensive, and up-to-date data on the locations of these services across the four-county region.

    Availability of Culturally Appropriate Health Care

    Cultural competence within the health care field is a key factor in reducing health disparities. Health care services that are respectful of and responsive to the health beliefs, practices and cultural and linguistic needs of diverse patients can help bring about more positive health outcomes. If a patient cannot communicate effectively with a medical practitioner, or feels unwelcome or uncomfortable, the patient may not receive necessary medical care. In addition, medical practitioners need to be able to incorporate a patient’s cultural beliefs, behaviors, practices, and needs into their diagnoses and intervention plans. While the availability of culturally appropriate health care is an important health equity issue, data was not available to enable us to map this indicator in a comprehensive way.

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    THEME: HEALTH OUTCOMES

     

    Other Relevant Indicators (not mapped)

    • Age-Adjusted Mortality and Life Expectancy Rates

     


    Health Outcomes: Body Mass Index

    Description: The Body Mass Index (BMI) is an indicator of levels of body fat based on an individual’s weight and height.  It does not measure the actual percentage of body fat, but instead reflects a proportional relationship and is often used to determine how much an individual’s body weight departs from what is normal or desirable for a person of a particular height.  In general, a BMI below 18.5 is considered underweight, a BMI between 18.5 – 24.9 is considered normal, a BMI between 25 – 29.9 is considered overweight, and a BMI of 30 or greater is considered obese.  Obesity has been linked to health outcomes such as cardiovascular disease and Type II diabetes.

    Data Source: OR Dept. of Motor Vehicles; data processed by OR Environmental Public Health Tracking System

    Data Limitations:This dataset is derived from Oregon driver’s license information (OR DMV) and is thus self-reported. It is likely that weight is also under-estimated (reflecting the tendency of persons to record a weight less than accurate).  Research indicates that the rate of under-reporting of weight in DMV records is relatively consistent, so the dataset is still useful for describing patterns.  It is best used for comparative purposes rather than a direct indicator of obesity levels at any given location. For a comprehensive statistical assessment on using the DMV records for health surveillance see the link below.

    [DMV Records are Valuable for Obesity Surveillance in Oregon]

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: 2010 Census Blockgroup

    Date of Data: 2003-2010 DMV Records

    Map Classification Scheme: Under the recommendation of the Oregon Health Authority, natural breaks were used for the relatively limited range of values in this dataset in order to delineate finder gradations rather than using the more generalized classes that are described above. This is consistent with the OHA/DMV report (linked above).

    Class/Values
    Description
    No Data No data available.
    BMI: 21.9 - 23.9 Considered normal.
    BMI: 23.91 - 24.6 Considered normal, but borderline overweight.
    BMI: 24.61 - 25.4 Considered overweight.
    BMI: 25.41 - 26.1 Considered overweight.
    BMI: 26.11 - 28 Considered borderline obese.

    Data Table Field Headings:

    Heading Description
    FIPS FIPS code for the census tract.
    med_BAll Median BMI (all).
    med_FAll Median BMI (female).
    med_MAll Median BMI (male).

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    Health Outcomes: Rate of Low Weight Births & Pre-Term Births

    • Rate of Low-Weight Births
    • Rate of Pre-Term Births

    Description: The Rate of Low-Weight Births and Pre-Term Births are a measure of birth outcomes and infant health. Data are collected from a variety of sources as part of the public health surveillance system. Low birth weight is defined as babies who weigh less than 5.5 pounds at birth (regardless of gestational age).  Pre-term births are births for which gestation is less than 37 weeks.  Individual data has been aggregated to the 2000 census tract level based on residence information indicated on the birth certificate or other health records.

    Data Source: Oregon Health Authority and Washington Department of Health (compiled from Vital Statistics Records)

    Data Limitations: In addition to low weight and pre-term births, measures of poor birth outcomes typically include very low-weight births, very pre-term births, and infant mortality. The sample sizes for these additional measures are not sufficiently large to enable them to be mapped at the census tract level. However, very low-weight births are included in the low-weight births measure and very pre-term births are included in the pre-term births measure.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: 2000 Census Tracts

    Date of Data: 2006-2010

    Map Classification Scheme: Rate of Low-Weight Births

    Class/Values
    Description
    0% Low-weight births as a percent of all births.
    0.01 - 4.84% Low-weight births as a percent of all births.
    4.85 - 6.56% Low-weight births as a percent of all births.
    6.57 - 8.64% Low-weight births as a percent of all births.
    8.65 - 16.13% Low-weight births as a percent of all births.

    Data Table Field Headings: Rate of Low-Weight Births

    Heading Description
    FIPS 2000 census tract ID.
    LBW_YEAR Data collection period.
    LBW_COUNT Low-weight births total count.
    LBW_POP Total births.
    LBW_PCT Low-weight births percent.

    Map Classification Scheme: Rate of Pre-Term Births

    Class/Values
    Description
    0% Pre-term births as a percent of all births.
    0.01 - 6.38% Pre-term births as a percent of all births.
    6.39 - 8.63% Pre-term births as a percent of all births.
    8.64 - 11.32% Pre-term births as a percent of all births.
    11.33 - 16.78% Pre-term births as a percent of all births.

    Data Table Field Headings: Rate of Pre-Term Births

    Heading Description
    FIPS 2000 census tract ID.
    PTB_YEAR Data collection period.
    PTB_BRTHRS Total births.
    PTB_POP Pre-term births total count.
    PTB_PCT Pre-term births percent.

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    Health Outcomes: Rates of Asthma, Diabetes and Cardiovascular Disease

    • Rate of Asthma: Dataset includes ages 5-50.
    • Rate of Diabetes: Dataset includes ages 18-75.
    • Rate of Cardiovascular Disease: Dataset includes ages 18-75.

    Rate of Asthma: Dataset includes participating insurance plan members ages 5-50 identified as having asthma during the measurement year or the year prior based on having a claim with an asthma diagnosis (493.XX) in any location OR having a pharmacy claim for asthma (based on HEDIS definition).

    Rate of Diabetes: Dataset includes participating insurance plan members ages 18-75 identified as having diabetes during the measurement year or the year prior according to either of the following HEDIS events:

    • Pharmacy Data - Members who were dispensed insulin or oral hypoglycemics/antihyperglycemics during the measurement year or year prior to the measurement year on an ambulatory basis.
    • Claim/Encounter Data - Members who had two face-to-face encounters with a diagnosis of diabetes on different dates of service in an outpatient setting or nonacute setting, or one face-to-face encounter in an acute inpatient or ED setting during the measurement year or the year prior to the measurement year. May count services that occur over both years.

    Rate of Cardiovascular Disease: Dataset includes participating insurance plan members ages 18-75 identified as having a cardiovascular condition, defined either through an event or a diagnosis.

    • Event - Member discharged alive for AMI, CABG or PTCA on or between 2-6 months prior to the measurement year.
    • Diagnosis - Member meets at least one of the following criteria during both the measurement year and the year prior: 1) At least one outpatient visit with any IVD diagnosis; 2) At least one acute inpatient visit with any IVD diagnosis.

    Data Source: Data on the indicators for Rates of Asthma, Diabetes and Cardiovascular Disease are compiled from insurer claims data submitted to Oregon Health Care Quality Corporation. Data include administrative claims (billing) data from eight commercial health plans, two Medicaid managed care plans and the Oregon Health Authority Division of Medical Assistance Programs (Medicaid).

    Data Limitations: Data is reported only for those patients that were continuously enrolled in a health plan that participates in the Oregon Health Care Quality Corporation’s measurement and reporting initiative or Medicaid fee-for-service during the measurement year, with no more than one gap of up to 45 days. Data does not include uninsured patients, patients who pay for their own health care services, Medicare fee-for-service patients, or patients served by a plan or Medicaid provider that does not supply data to Quality Corp. The data, therefore, do not represent all persons living within a census tract or neighborhood.

    Data on rates of asthma, diabetes and cardiovascular disease were geocoded by patient addresses. However, in order to maintain confidentiality, the data were aggregated into either census tracts or neighborhoods. If the number of records failed to meet a minimum sample size threshold the data were not reported (indicated by a 999 in the attribute table). The sample size threshold that was used was based on the recommendations outlined by the CDC in their National Center for Health Statistics Staff Manual on Confidentiality. Based on this threshold, data from geographies where the numerator was less than 5 people, or the difference between the denominator and numerator was less than 5 people, were suppressed. As an example, if a geography had 50 patients in the denominator then it was reportable so long as the numerator was between 5 – 45. Additionally a denominator threshold of 25 was applied to ensure robust reported rates.

    Some patient records did not have complete patient street addresses. If the street address could not be accurately located within the aggregated geography, those patient records were not mapped.

    Clark County Data: Although the data for this indicator include information for some Clark County census tracts and neighborhoods, these data are less reliable than the data for Multnomah, Clackamas, and Washington counties and should be used with caution. The focus of Oregon Health Care Quality Corporation's work is in Oregon. Some of the participating health plans submit claims data for members living in Clark County, but many do not. For this reason the Clark County results are based on a narrow population of Clark County residents, and the health care/outcome results may not be representative of the larger population.

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

    Geographic Unit: 2010 Census Tracts and Neighborhoods

    Date of Data: Measurement Year 1/1/2011 - 12/31/2011

    Map Classification Scheme: Rate of Asthma (census tract and neighborhood)

    Class/Values
    Description
    3.11 - 10.49% Percent of all eligible patients identified as having asthma during the measurement year.
    10.5 - 13.09% Percent of all eligible patients identified as having asthma during the measurement year.
    13.1 - 16.12% Percent of all eligible patients identified as having asthma during the measurement year.
    16.13 - 25% Percent of all eligible patients identified as having asthma during the measurement year.
    Data Not Available (999) Data is not reported. Sample in geographic unit did not meet confidentiality threshold.

    Data Table Field Headings: Rate of Asthma (census tract and neighborhood)

    Heading Description
    ID FIPS code for census tract or neighborhood name.
    p_ASTHMA Percent of all eligible patients identified as having asthma during the measurement year.

    Map Classification Scheme: Rate of Diabetes(census tract and neighborhood)

    Class/Values
    Description
    0 - 6.1% Percent of total eligible patients with diabetes.
    6.2 - 7.8% Percent of total eligible patients with diabetes.
    7.9 - 11.5% Percent of total eligible patients with diabetes.
    11.6 - 19.7% Percent of total eligible patients with diabetes.
    Data Not Available (999) Data is not reported. Sample in geographic unit did not meet confidentiality threshold.

    Data Table Field Headings: Rate of Diabetes (census tract and neighborhood)

    Heading Description
    ID FIPS code for census tract or neighborhood name.
    p_diabetes Percent of patients with diabetes.

    Map Classification Scheme: Rate of Cardiovascular Disease (census tract and neighborhood)

    Class/Values
    Description
    0.57 - 1.5% Percent of total eligible patients with cardiovascular disease.
    1.51 - 2.2% Percent of total eligible patients with cardiovascular disease.
    2.21 - 3.8% Percent of total eligible patients with cardiovascular disease.
    3.81 - 7.8% Percent of total eligible patients with cardiovascular disease.
    Data Not Available (999) Data is not reported. Sample in geographic unit did not meet confidentiality threshold.

    Data Table Field Headings: Rate of Cardiovascular Disease (census tract and neighborhood)

    Heading Description
    ID FIPS code for census tract or neighborhood name.
    p_HeartDis Percent of patients with cardiovascular disease.

     

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    Description of Other Relevant Health Outcome Indicators (not mapped)

    Age-Adjusted Mortality and Life Expectancy Rates

    One of the most important measures of a person’s health is how long that person lives. Systematic differences in age-adjusted mortality and life expectancy rates across populations can be a key indication of underlying health disparities.  While mortality and life expectancy information can be gleaned from death certificate data, an analysis of this data determined that the sample sizes were not sufficient to permit the data to be meaningfully mapped at a neighborhood level.

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    THEME: HEALTHY ENVIRONMENT

     

    Other Relevant Indicators (not mapped)

    • Compromised Environments
    • Water Quality
    • Green Infrastructure
    • Climate Change

    Healthy Environment:
    Air Quality: Number of Times Level Above Benchmark (for various sources of air toxins)

    Description: The Air Quality indicators were developed by the Oregon Department of Environmental Quality's (DEQ) Portland Air Toxics Solutions Project (PATS). The study uses both modeling of future emissions and current monitoring to ascertain where air toxics concentrations are likely to exceed safety benchmarks in 2017. For more information see the DEQ PATS website.

    DEQ data available for:

    • All Sources
    • Road Sources
    • Non-Road Sources
    • Residential Wood Fires
    • Point Sources
    • Area Sources

    Data Limitations: The data used for the Air Quality maps are the best data available, but it should be noted that some of the data is based on modeling rather than actual measurements. DEQ collects monitoring data to assess which pollutants currently exceed benchmarks near the existing air quality monitoring locations. However, monitoring locations are limited, and emissions change over time with population growth, economic growth, and regulatory emission controls. Therefore, DEQ uses both modeling of future emissions and current monitoring to develop future models. Air quality modeling allows DEQ to estimate concentrations in areas where there are no air monitors and to estimate concentrations for pollutants that are not or cannot be measured at monitors.

    Data Source: Oregon Department of Environmental Quality

    Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon)

    Geographic Unit: Polygons based on an original rasterized dataset.

    Date of Data: Modeled for Year 2017

    Map Classification Scheme: Classification scheme is the same for all DEQ datasets.

    Class/Values
    Description
    1 to 5 Toxic levels above benchmarks 1-5 times in modeled year.
    6 to 10 Toxic levels above benchmarks 6-10 times in modeled year.
    11 to 20 Toxic levels above benchmarks 11-20 times in modeled year.
    21 to 40 Toxic levels above benchmarks 21-40 times in modeled year.
    41 to 60 Toxic levels above benchmarks 41-60 times in modeled year.
    61 to 80 Toxic levels above benchmarks 61-80 times in modeled year.
    81 to 120 Toxic levels above benchmarks 81-120 times in modeled year.
    121 to 170 Toxic levels above benchmarks 121-170 times in modeled year.

    Data Table Field Headings: These data layers have no additional field attributes. Refer to the link above (PATS) for more information about interpreting the data.

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    Healthy Environment: Green Infrastructure

    Description: The Green Infrastructure indicator was compiled using 3 datasets and multiple scoring categories based on the the amount of vegetation or the presence/absence of other key "green" features.The map represents the total score (combining all 3 datasets) and ranges from 0 to 8. The greater the value the greater the green infrastructure that is present at that location.

    The datasets include a tree canopy and low-level vegetation raster that indicates the percent of these features in a given raster cell, polygon layers of the location of ecoroofs and green streets, and a polygon layer of the Natural Resource Inventory (NRI) Combined Relative Resource Value (that indicates the level -- low to high -- of a combination of riparian and wildlife habitat).

    Note: Green streets are those street segments that include a rain garden or bioswale designed to collect or otherwise mitigate stormwater runoff.

    The scoring is as follows:

    0 - Less than 50% low-level vegetation and less than 10% canopy (calculated from vegetation/canopy dataset).

    1 - 50% or greater low-level vegetation and less than 10% canopy (calculated from vegetation/canopy dataset).

    1 - Less than 50% low-level vegetation and between 10% and 49% canopy (calculated from vegetation/canopy dataset).

    2 - 50% or greater low-level vegetation and between 10% and 49% canopy (calculated from vegetation/canopy dataset).

    2 - Green streets (green street present = 2; not present = 0).

    3 - Ecoroofs (ecoroof present = 3; not present = 0).

    3 - NRI areas of medium and high combined value (NRI value of medium or high constitutes 50% or more of the analysis grid cell area = 3; under 50% = 0).

    Data Processing: A 264' x 264' raster of the City of Portland was used as the analysis layer (with water features removed). For the vegetation/canopy score, the zonal statistics tool was run to determine the percentage of vegetation/canopy cell values within each analysis grid cell (sum of vegetation cover pixels/total pixel count per analysis cell). The grid cells were then scored according to the percentages of low-level vegetation and canopy that occupy each cell as indicated above. Ecoroofs and green streets were scored according to whether they intersected an analysis grid cell (only those that intersected received a score as indicated above). The NRI layer was compared to the analysis grid. A calculation was made to determine if NRI values of high or medium constituted 50% or more of the analysis grid cell. If so, the cell was assigned a score of 3. The scores were totalled and a new raster grid created reflecting these scores.

    Data Limitations: Because this raster layer represents a composite score for a combination of green features, it cannot be used to determine the "ratio" or extent of any given green feature at a particular location (for example, you cannot determine whether a high score is the result of heavy vegetation canopy or the presence of several ecoroofs).

    The green infrastructure indicator was constructed from data layers that were readily available for the City of Portland and may not include all "green" features. In addition, the scoring criteria, though not arbitrary, represents ony one possible framework (for example, some may not "value" ecoroofs or green streets at the level indicated in this composite indicator or would consider 50% vegetation too low).

    Data Sources:

    Ecoroofs & Green Streets: Portland Bureau of Environmental Services (BES)

    Natural Resource Inventory (NRI): Portland Bureau of Planning & Sustainability (BPS)

    Canopy/Vegetation Layers: Portland Bureau of Environmental Services (BES)

    Geographic Extent: City of Portland

    Geographic Unit: Raster (264' cell size)

    Dates of Data:

    Ecoroofs (BES): 2007-current (last update 12/26/2012)

    Green Streets (BES): 2006-current (last update 4/25/2013)

    Natural Resource Inventory (BPS): 2007-current (no date available for last update)

    Canopy/Vegetation Layer (BES): June 2002

    Map Classification Scheme: This raster layer displays a ranking of green infrastructure features ranging from 1 to 5. A rank of 1 means no green features or the cell is not in the study area. The remaining ranks (from 2-5) are based on the range of scores (1-8) as indicated in the table below. Blues represent low scores. Browns represent high scores.

    Rank Description
    1 No Green Features or Not in Study Area (0)
    2 Low Score (1)
    3 Medium Score (between 2-3)
    4 Medium-High Score (between 4-6)
    5 High Score (between 7 and 8)

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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      Description of Other Relevant Environment Indicators (not mapped)

      Compromised Environments

      A growing body of research shows that low-income households, particularly communities of color, often bear greater environmental and health risks than the general population. These communities are often exposed to higher levels of environmental toxins because of the proximity of their homes to brownfields, toxic waste sites, industrial areas, and superfund sites.  The Environmental Protection Agency’s Toxic Release Inventory provides data on the locations of businesses and other facilities that have been cited for the disposal or other releases of over 650 toxic chemicals. However, an analysis of the TRI data for this project determined that the TRI data on its own do not provide the level of detail necessary for mapping exposure to environmental toxins in a meaningful way.  This indicator is in a developmental stage, and we hope to add it to the Equity Atlas in the future.

      Water Quality

      Access to clean drinking water is an important public health issue. Access to healthy rivers, lakes, and streams also has a significant impact on the health of populations who rely on fishing as a key source of nutrition. These populations tend to be disproportionately low-income and people of color, making this an important equity issue. Access to healthy rivers, lakes, and streams also enhances the health benefits associated with exposure to natural habitat. While water quality testing data is available, developing a methodology for effectively mapping this data is complex. This indicator is in a developmental stage, and we hope to add it to the Equity Atlas in the future.

      Green Infrastructure - Regional

      The Equity Atlas measures proximity to parks and natural areas that are accessible to the public, but there are also benefits from living in an area that has plentiful sources of “green”, regardless of whether residents can physically access those greenspaces.  This “green infrastructure” includes parks and natural areas, tree canopy, grass, shrubs, ecoroofs, green streets, and any other sources of neighborhood greening. The benefits of green infrastructure include improved air quality, reduced heat in the summer, and environmental benefits such as reduced stormwater pollution. Comprehensive data on green infrastructure are not available in a format that would enable us to map this indicator at a regional scale. Comprehensive data are available for the city of Portland, and the Atlas includes a pilot map of Green Infrastructure for Portland. Our hope is that this pilot map will inspire efforts to collect sufficient data at a regional scale to enable a similar map to be developed for the entire region.

      Climate Change

      The impacts of climate change will affect the health and livability of neighborhoods throughout the region, but some neighborhoods and populations will be harder hit than others. Mapping the anticipated impacts of climate change could help to inform efforts to ensure that the burdens of climate change do not disproportionately harm specific populations or neighborhoods. However, insufficient modeling data is available to enable us to map this issue, and developing this data was beyond the scope of this project.

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      THEME: HOUSING

       

      Other Relevant Indicators (not mapped)

      • Gentrification and Displacement
      • Fair Housing
      • Housing Quality
      • Homelessness
      • Regulatory Access
      • Utility Costs
      • Location of Section 8 Households

       


       

      Housing: Housing Affordability

      Description: The Housing Affordability indicators explore Median Home Values, Rental Costs, and Housing Purchasing Power.
       

      HOUSING AFFORDABILITY: MEDIAN HOME VALUE (Sales Price)

      Description: The Median Home Value indicator is derived from the tax assessor databases in the tri-county metro region and Clark County. The sales price (as opposed to the assessed value) is used to calculate the median home value because sales price is a more accurate reflection of housing costs and market value.

      For more detailed information about how the median home values were compiled see the link below:

      [Link to Additional Metadata on Housing Affordability and Median Home Value]

      Data Source: Metro RLIS and Clark County GIS (tax assessors databases)

      Data Limitations: Because this indicator is based on sales price data, it only captures information on homes that were sold and are in the database.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: 2010 Census Tracts

      Date of Data: 2011 Metro; 2010 Clark Co.

      Map Classification Scheme:

      Class/Values
      Description
      $139,283 - 257,149 Median home value.
      $257,150 - 370,780 Median home value.
      $370,790 - 535,467 Median home value.
      $535,468 - 806,160 Median home value.

      Data Table Field Headings:

      Heading Description
      ID Census tract FIPS code.
      CURVAL Current median home value.

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      HOUSING AFFORDABILITY: PERCENT CHANGE IN MEDIAN HOME VALUE (2000-2010)

      Description: The Percent Change in Median Home Value indicator shows the percent change in home value between 2000 and 2010. The average home values (by census tract) are based on the recorded sales prices of owner-occupied single family homes on less than 10 acres in 2000 and in 2010. The value is calculated by taking the difference between the average home values in 2010 and 2000 (adjusted for inflation) then dividing the difference by the average 2000 home value.

      For more detailed information about how the median home values were compiled see the link below:

      [Link to Additional Metadata on Housing Affordability and Median Home Value]

      Data Source: Metro RLIS and Clark County GIS (tax assessors databases)

      Data Limitations: Because this indicator is based on sales price data, it only captures information on homes that were sold and are in the database.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: 2010 Census Tracts

      Date of Data: 2000 and 2010 (Tax Assessor Database)

      Map Classification Scheme:

      Class/Values
      Description
      -0.47% to -1% Percent decrease in home value between 2000 and 2010.
      0% No change in average home value between 2000 and 2010.
      .1% to 50% Percent increase in home value between 2000 and 2010.
      50.1% to 75% Percent increase in home value between 2000 and 2010.
      75.1% to 100% Percent increase in home value between 2000 and 2010.
      Over 100% Percent increase in home value between 2000 and 2010.

      Data Table Field Headings:

      Heading Description
      ID Census tract FIPS code.
      INFAFF The affordability of a home based on median income and median home value expressed as a percent.
      VALCHG The percent change in home value between 2000 and 2010.

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      HOUSING AFFORDABILITY: MEDIAN RENTAL COST (2-Bedroom Units)

      Description: The Median Rental Cost indicator shows data from a Metro Multifamily Housing Association Apartment Survey that gathered information about rental rates in 2011.

      Data Source: Metro Multifamily Housing 2011 Apartment Survey

      Data Limitations: The data for this indicator are based on the responses to a survey that was sent out to multi-family properties in the metro area that are on the mailing list of the Metro Multifamily Housing Association. 1,072 properties responded to the survey, and their responses were aggregated by zip code. These properties represent a sub-sample of the total number of multi-family properties in the four-county region, and the sampling methodology was not scientific. Therefore, it is unknown whether the median rental costs based on the sample are an accurate reflection of median rental costs for all rental units in each zip code.

       

      Rental rates are often sensitive to the market and can fluctuate significantly from year to year. For example, when home sales increase, the demand for rental units decreases and the rental rates, on average, go down.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: Zipcodes

      Date of Data: Survey Data gathered 02-07-12 through 03-15-12 (reflecting 2011 average rents)

      Map Classification Scheme:

      Class/Values
      Description
      $479.00 - $650.00 Average rent per month.
      $650.01 - $779.00 Average rent per month.
      $779.01 - $900.00 Average rent per month.
      $900.01 - $1150.00 Average rent per month.
      $1150.01 - $1579.00 Average rent per month.

      Data Table Field Headings:

      Heading Description
      ZIPCODE Zipcode.
      Min_Rent Minimum rent reported in this zipcode.
      Max_Rent Maximum rent reported in this zipcode.
      Median_R Median rent for this zipcode.

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      HOUSING AFFORDABILITY: HOUSING PURCHASING POWER (Comparing Median Household Income with Median Home Sales Price)

      Description: The Housing Affordability indicator shows the ratio of estimated housing purchasing power to housing costs by census tract. It is calculated by comparing the census tract's median household income to the median price of single-family homes in each census tract. "Housing purchasing power" is based on the 2010 median housing income and the contemporary lending climate (2011/2012). Low percentages indicate places where current residents could potentially afford to purchase a home for sale in their area, if they were in the market to do so (low divergence between housing costs and housing purchasing power); high percentages indicate places where current residents are less likely to be able to afford to purchase an existing home for sale in their area (high divergence between housing costs and housing purchasing power).

      Data Source: Portland Metro and Clark County GIS (tax assessors database); 2000 US Census Data and 2010 ACS Data (income)

      Data Limitations: This indicator provides a general indication of whether the housing in a given census tract is more or less affordable. Because it focuses on home sales price, it does not provide a good indication of the affordability of rental housing. Therefore, the Median Rental Cost indicator should be viewed in combination with the data in this indicator.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: 2010 Census Tracts

      Date of Data: 2000-2010

      Map Classification Scheme:

      Class/Values
      Description
      0 - 40% (most affordable) Low divergence between housing costs and housing purchasing power.
      40 - 50% Medium-Low divergence between housing costs and housing purchasing power.
      50 - 68.5% Medium divergence between housing costs and housing purchasing power.
      80 - 100% Medium-High divergence between housing costs and housing purchasing power.
      100 - 148.5% (least affordable) High divergence between housing costs and housing purchasing power.

      Data Table Field Headings:

      Heading Description
      INFAFF Divergence between housing costs and housing purchasing power.
      VALCHG The percent change in home value between 2000 and 2010.

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      Housing: Minority Homeownership Gap

      Description: The Minority Homeownership Gap indicator reflects the disparity in regional home-ownership rates between Whites and minorities (defined as anyone except non-Hispanic Whites).  The “gap” is calculated by the following formula:  minority households as a percentage of all households minus minority home-owning households as a percentage of all home-owning households.  If minority home-ownership rates were equal to or greater than the minority population size, the “gap” would equal 0 or less.  Positive numbers indicate a minority homeownership gap (the larger the number the greater the gap).

      Data Source: Census 2010

      Data Limitations: Because of the way the gap is calculated, areas with a higher percentage of minority households often have a larger minority homeownership gap. This is a legitimate finding, but the dynamic should be kept in mind when viewing the maps.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: Census Blockgroup

      Date of Data: 2010

      Map Classification Scheme:

      Class/Values
      Description
      No Gap No minority homeownership gap.
      0.01 to 3.13 Percent gap in minority ownership.
      3.14 to 7.5 Percent gap in minority ownership.
      7.51 to 14.5 Percent gap in minority ownership.
      14.51 to 18.1 Percent gap in minority ownership.
      Greater than 18.1 Percent gap in minority ownership.

      Data Table Field Headings:

      Heading Description
      FIPS Census blockgroup FIPS code.
      HOG100 Minority homeownership gap percent.

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      Housing: Housing Accessibility

      Description: The Housing Accessibility indicators show different types of housing that may be more accessible to persons with disabilities (single story or elevator buildings) and the low-income population (subsidized housing).

       

      HOUSING ACCESSIBILITY: DENSITY OF SINGLE STORY HOUSING AND ELEVATOR BUILDINGS AS PROXY FOR HOUSING ACCESSIBILITY

      Description: The Density of Single Story Housing and Elevator Buildings (as a proxy for housing accessibility for persons with physical disabilities) indicator shows the density of these types of housing units.

      Data Source: Metro analysis of RLIS data (for Clackamas, Washington and Multnomah counties) and Clark County GIS taxlot data (for Clark County)

      The following methodology was used to generate the data on single story housing: For RLIS data: (a) take the highest building on a taxlot (in order to filter out single story detached garages); (b) select buildings with average heights of 15 feet; (c) reselect the selected features to get rid of buildings in zones that don't allow residential development; (d) convert to points. For Clark County data: (a) select taxlots with a building type of "Ranch"; (b) convert to points.

      To generate the data on elevator buildings, addresses were pulled for all multi-story/multi-unit residential buildings constructed after 1990 and then converted to points.

      Data Limitations: Comprehensive data is not available that would enable us to map the locations and densities of handicapped accessible housing units in the metro area. This indicator provides a reasonable, but limited, proxy by showing single story houses and multi-unit residential buildings with elevators. However, not all of the units included in the indicator may actually be accessible because of the presence of other impediments such as stairs leading to the front door, doorways that are too narrow for wheelchairs, etc.

      The methodology used to determine which buildings have elevators was relatively rough, and likely missed some buildings. All non-single family buildings constructed after the ADA went in effect in 1990 are required to meet accessibility requirements. Therefore, we assumed that any multi-story buildings constructed after 1990 have elevators. However, some multi-story buildings that were constructed before 1990 have elevators, particularly if they were renovated after 1990. Those buildings were not captured in our definition. Furthermore, the year built is not available for about 1,000 of the records in Metro’s multi-family housing database, so those buildings were not included.

      Other potential limitations:

      • False positives:  A few low buildings in mixed use areas might have been falsely classified as single-story houses in the method that was used to analyze the RLIS data. 
      • Not weighted by units:  There is one point per building, which means that buildings with multiple units (either multi-story or garden apartments) are weighted the same as single-family houses.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon); Clark County (Washington)

      Geographic Unit: Density Raster (264' cell size)

      Date of Data: 2012

      Map Classification Scheme (Density): Density rasters are displayed using a 1-5 classification scheme based on the natural breaks in the value range. Blues represent low density. Browns represent high density.

      Rank
      Description
      1 Low
      2 Medium Low
      3 Medium
      4 Medium High
      5 High

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for density raster layers. Additional spreadsheet data is not available for this indicator.

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      HOUSING ACCESSIBILITY: LOCATION OF PUBLICLY-SUBSIDIZED AFFORDABLE HOUSING

      Description: The Publicly-Subsidized Affordable Housing indicator shows the location of housing units that are made affordable through public subsidies and/or agreements or statutory regulations that restrict or limit resident income levels and/or rents. Publicly-subsidized (also referred to as "regulated") affordable housing generally provides housing for households that otherwise could not afford adequate housing at market rates.

      Data Source: Metro's 2011 Regional Inventory of Regulated Affordable Housing

      Data Limitations: The data do not include non-regulated (i.e. private market) housing units that provide housing that is affordable to low-income residents. The data also do not include the locations of Section 8 voucher holders who receive publicly subsidized vouchers which keep their housing affordable, but who can use those vouchers in private units.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: Graduated Points

      Date of Data: 2011

      Map Classification Scheme:

      Class/Values
      Description
      1 - 102 Indicates a range of the number of units at that location.
      103 - 204 Indicates a range of the number of units at that location.
      205 - 305 Indicates a range of the number of units at that location.
      306 - 407 Indicates a range of the number of units at that location.
      408 - 508 Indicates a range of the number of units at that location.
      509 - 610 Indicates a range of the number of units at that location.

      Data Table Field Headings:

      Heading Description
      Proj_Name Name of the housing project.
      Proj_Addr Address of the housing project.
      City City of the housing project.
      State State of the housing project.
      Zip Zipcode of the housing project.
      Spnsr_Name Name of the primary sponsoring organization or agency.
      Spnsr_Type Government, Non-Profit, For-Profit
      Const_Type Description of the type of building construction (e.g. Low Rise Apts, Townhouses).
      Proj_Type Acquisition, Rehab, New Construction, Preservation, Predevelopment, No Construction
      Units Number of subsidized units.
      Reg_Units Number of non-subsidized units.

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      Housing: Housing Cost Burden

      Description: The Housing Cost Burden indicators show areas where (a) the percent of income spent on a combination of housing and transportation costs and (b) over 35% of annual income is spent on meeting housing costs.

       

      HOUSING COST BURDEN: HOUSING AND TRANSPORTATION COST BURDEN

      Description: The Housing and Transportation Cost Burden indicator uses a combination of American Community Survey data, Bureau of Labor Statistics Consumer Expenditure Survey data and other sources to model average housing and transportation costs as a percent of annual household income. The data include all annual housing costs comprising mortgages, property taxes, maintenance, rents, utilities, household operations, supplies and appliances/furnishing. Transportation costs include all annual transportation costs (including public transit costs). The threshold for "cost burdened" is defined as between 45-55% depending on income level (35% for housing and 15% for transportation).

      Data Source: MetroScope Housing Needs Analysis

      [Link to MetroScope HNA Report Here]

      Data Limitations: Because the data for this indicator are based on complex economic models (using ACS and BLS sample data), it is not possible to determine the margins of error for the data.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: Metro Housing Needs Analysis Subareas (these are aggregations of census tracts)

      Date of Data: Census tract-level estimates of dwelling units by single family and multi-family are from 2005. Demographic (income, age, household size) and housing data (housing type by value class) are taken from the 2000 Census. Updating to 2005 and matching demographics to housing by value class are computed within MetroScope.

      Map Classification Scheme:

      Class/Values
      Description
      36.9% - 40% Housing and transportation costs as a percent of income.
      40.0% - 43% Housing and transportation costs as a percent of income.
      43.0% - 46% Housing and transportation costs as a percent of income.
      46.0% - 49% Housing and transportation costs as a percent of income.
      49.0% - 53% Housing and transportation costs as a percent of income.

      Data Table Field Headings:

      Heading Description
      HNA_Area Housing needs assessment area code.
      Total_DU Total dwelling units.
      Avg_Inc Average annual household income for the geographic unit.
      AvgTrans Average annual cost for transportation for the geographic unit.
      AvgHouse Average annual cost for housing for the geographic unit.
      Pct_Trans Transportation cost as a percent of average annual income.
      Pct_House Housing cost as a percent of average annual income.
      Pct_Both Transportation and housing cost as a percent of average annual income.
      HNA_Name Name of the housing needs assessment area.

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      HOUSING COST BURDEN: SPENDING OVER 35% OF INCOME ON HOUSING (renters and homeowners)

      • Percent Renters Spending over 35% of Income on Housing
      • Percent Owners (without mortgage) Spending over 35% of Income on Housing
      • Percent Owners (with mortgage) Spending over 35% Income on Housing

      Description: The Housing Cost Burden indicators show the percent of renters or homeowners that spend over 35% of their household income on housing costs. When housing costs exceed 30-35% of household income, then the housing is commonly considered unaffordable for that household.

      Data Source: American Community Survey (ACS); DP04 Selected Housing Characteristics

      Data Limitations: Housing costs in the ACS survey include only mortgage or rent payments, condominium membership and other fees, real estate taxes, and premiums for homeowner's insurance (if included in the mortgage). This data does not include utilities.

      Because of sample size issues, the margin of error tends to be quite high when disaggregating ACS data. Consequently, the housing cost burden indicators are mapped at the PUMA level -- a relatively coarse geographic unit, but one where the margins of error are at an acceptable level. The maps can be used to discern general regional patterns only.

      The attribute table contains information on the margins of error and should be consulted before using this data for any analyses. A composite spreadsheet with all the ACS housing cost burden data can be downloaded using the link below.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: PUMA

      Date of Data: ACS 5-year estimates (2006-2010)

      Map Classification Scheme: Percent Renters Spending over 35% of Income on Housing

      Class/Values
      Description
      32% - 35% Percent of renters spending over 35% of income on housing.
      36% - 43% Percent of renters spending over 35% of income on housing.
      44% - 52% Percent of renters spending over 35% of income on housing.

      Data Table Field Headings: Percent Renters Spending over 35% of Income on Housing

      Heading Description
      PUMA PUMA FIPS code.
      PRentC35 Percent of renters spending over 35% of income on housing.
      PRentC35MO Margin of error for percent renters spending over 35% of income on housing.

      Map Classification Scheme: Percent Owners (without mortgage) Spending over 35% of Income on Housing

      Class/Values
      Description
      9% - 11% Percent owners (without mortgage) spending over 35% of income on housing.
      12% - 14% Percent owners (without mortgage) spending over 35% of income on housing.
      15% - 18% Percent owners (without mortgage) spending over 35% of income on housing.

      Data Table Field Headings: Percent Owners (without mortgage) Spending over 35% of Income on Housing

      Heading Description
      PUMA PUMA FIPS code.
      PNoMC35 Percent owners (without mortgage) spending over 35% of income on housing.
      PNoMC35MOE Margin of error for percent owners (without mortgage) spending over 35% of income on housing.

      Map Classification Scheme: Percent Owners (with mortgage) Spending over 35% of Income on Housing

      Class/Values
      Description
      26% - 27% Percent owners (with mortgage) spending over 35% of income on housing.
      28% - 32% Percent owners (with mortgage) spending over 35% of income on housing.
      33% - 38% Percent owners (with mortgage) spending over 35% of income on housing.

      Data Table Field Headings: Percent Owners (with mortgage) Spending over 35% of Income on Housing

      Heading Description
      PUMA PUMA FIPS code.
      PMortC35 Percent owners (with mortgage) spending over 35% of income on housing.
      PMortC35MO Margin of error on percent owners (with mortgage) spending over 35% of income on housing.

      Link to Data [Excel Spreadsheet]

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      Housing: Access to Home Loans

      Description: The Access to Home Loand indicators show access to home loans as well as loan denials. The HMDA (Home Mortgage Disclosure Act) requires lending institutions to report public loan data. This indicator compiles data from the LAR reports (Loan Application Register) which record information on the type of loan application, race and ethnicity of applicants (using standard census race/ethnicity categories) and status of application loan (e.g. approved or denied).

      Data Source: FFIEC (Federal Financial Institutions Examinations Council) HMDA Database

      Data Limitations: The data do not capture information on people who may not have applied for a loan to begin with because of economic or other barriers or the perception that they would be denied. The loan denial information also does not provide adequate information on the reasons for the loan denial.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: 2000 Census Tracts

      Date of Data: 2011

      ACCESS TO HOME LOANS: NUMBER OF APPLICATIONS FOR CONVENTIONAL OR FHA LOANS

      Map Classification Scheme: Number of Applications for Conventional Loans

      Class/Values
      Description
      3 - 201 Number of applications for conventional loans.
      202 - 390 Number of applications for conventional loans.
      391 - 763 Number of applications for conventional loans.
      764 - 2094 Number of applications for conventional loans.

      Data Table Field Headings: Number of Applications for Conventional Loans

      Heading Description
      FIPS Census tract FIPS code.
      ToApLo1 Total conventional loan applications.

      Map Classification Scheme: Number of Applications for FHA Loans

      Class/Values
      Description
      0 to 47 Total number of applications for FHA loans.
      48 to 91 Total number of applications for FHA loans.
      92 to 150 Total number of applications for FHA loans.
      151 to 300 Total number of applications for FHA loans.

      Data Table Field Headings: Number of Applications for FHA Loans

      Heading Description
      FIPS Census tract FIPS code.
      ToApLo2 Total FHA loan applications.

       

      ACCESS TO HOME LOANS: HOME LOAN DENIALS

      Map Classification Scheme: Home Loan Denials (White Non-Hispanic Only)

      Class/Values
      Description
      0% - 10% Percent of loan denials for White, Non-Hispanic only.
      10.1% - 15% Percent of loan denials for White, Non-Hispanic only.
      15.1% - 20% Percent of loan denials for White, Non-Hispanic only.
      20.1% - 31% Percent of loan denials for White, Non-Hispanic only.

      Data Table Field Headings: Home Loan Denials (White Non-Hispanic Only)

      Heading Description
      FIPS Census tract FIPS code.
      TotAppW Total applications (White Non-Hispanic)
      TotDenW Total loan denials (White Non-Hispanic)
      PctDenW Percent of loan denials (White Non-Hispanic)

      Map Classification Scheme: Home Loan Denials (Non-White, including Hispanic)

      Class/Values
      Description
      0% - 10% Percent of loan denials for Non-White, including Hispanic.
      10.1% - 15% Percent of loan denials for Non-White, including Hispanic.
      15.1% - 20% Percent of loan denials for Non-White, including Hispanic.
      20.1% - 31% Percent of loan denials for Non-White, including Hispanic.
      31.1% - 50% Percent of loan denials for Non-White, including Hispanic.
      50.1% - 100% Percent of loan denials for Non-White, including Hispanic.

      Data Table Field Headings: Home Loan Denials (Non-White, including Hispanic)

      Heading Description
      FIPS Census tract FIPS code.
      TotAppNW Total applications (Non-White, including Hispanic)
      TotDenNW Total loan denials (Non-White, including Hispanic)
      PctDenNW Percent of loan denials (Non-White, including Hispanic)

      Map Classification Scheme: Home Loan Denials (All Applications)

      Class/Values
      Description
      0% - 10% Percent of loan denials (all applications).
      10.1% - 15% Percent of loan denials (all applications).
      15.1% - 20% Percent of loan denials (all applications).
      21.1% - 40% Percent of loan denials (all applications).

      Data Table Field Headings: Home Loan Denials (All Applications)

      Heading Description
      FIPS Census tract FIPS code.
      Total_App Total applications.
      Tot_Den Total loan denials.
      PctDenALL Percent of loan denials.

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      Housing: Foreclosures (Percent Notice of Transfer Sales - RealtyTrac)

      Description: The Foreclosure indicator shows the percentage of households per zipcode that received a Notice of Transfer Sale as part of the foreclosure process.

      Click on the link below for detailed information about the RealtyTrac Foreclosure Inventory Report.

      [RealtyTrac Foreclosure Inventory Report]

      Data Source: RealtyTrac

      Data Limitations: Data is based on the NTS (notice of transfer sale) rather than REO (real estate owned by the lender) data as the NTS data reflects fully foreclosed properties. This results in lower percentages (only properties fully foreclosed) rather than the higher numbers of properties that may have started the process, but were able to move out of foreclosure.

      The data do no include demographic information about the owner or the reasons for the foreclosure.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon), Clark County (Washington)

      Geographic Unit: Zipcode

      Date of Data: 2011

      Map Classification Scheme:

      Class/Values
      Description
      0% to 0.3% Percent foreclosures.
      0.4% to 0.7% Percent foreclosures.
      0.8% to 1.6% Percent foreclosures.

      Data Table Field Headings:

      Heading Description
      ZIPCODE Zipcode.
      NTS Number of Notice of Transfer Sales.
      Tot_hshld Total households.
      PCT_NTS Percent of Notice of Transfer Sales.

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      Housing: Housing Tenure

      • Homeowners
      • Renters
      • Vacant Units

      Description: The Housing Tenure indicators show the density (persons per acre) of those indicating that they are either renters or homeowners. An additional layer shows the number of vacant units (defined as a valid address recorded with the US Census Bureau that has no occupant).

      Data Source: U.S. Census 2010 (H4 Tenure); Universe = Total Housing Units

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Density Raster (264' cell size)

      Date of Data: 2010

      Data Processing: An "ecumene" mask was created to remove areas of no residential population prior to creating the rasters. Click on the link below for a slideshow documenting how the census rasters were processed.

      Census Rasters Data Processing Slideshow

      Map Classification Scheme (Density): Density rasters based on census block data are displayed using a 1-5 classification scheme. For the Renters, Owners and Vacant rasters, a ranking of 1 is always used to indicate cells with no residential population. Natural Breaks are used to create the remaining 4 classes (ranked 2-5) based on the range of values. Blues represent low density. Browns represent high density.

      Classification Scheme Limitations: The Renters, Owners and Vacant indicators show the density (per acre) of the different tenure categories based on a 1-5 classification scheme where 2 represents the lowest densities and 5 represents the highest densities. The classification schemes between the various indicators are relative rather than absolute (or standardized). This means that a classification of “5” in the Owners map, while it represents the areas with the highest densities of homeowners in the metro region, does not represent the same range of values as the areas classified a “5” in the Renters indicator. Therefore, it is not advisable to make side-by-side comparisons between the tenure maps. They should be used independently.

      Homeowners (homeowners density per acre)

      Rank Description
      1 No resident population.
      2 0.01% to 45.16%
      3 45.17% to 69.49%
      4 69.5% to 88.39%
      5 88.4% to 100%

      Renters (renter density per acre)

      Rank Description
      1 No resident population.
      2 0.01% to 28.99%
      3 29% to 52.94%
      4 52.95% to 80.82%
      5 80.83% to 100%

      Vacant Units (vacant units density per acre)

      Rank Description
      1 No resident population.
      2 0.1% to 12.2%
      3 12.3% to 29.8%
      4 29.9% to 68.4%
      5 68.5% to 100%

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download the Excel spreadsheet for the full dataset that includes the FIPS code and raw counts for all tenure categories.

      Link to Data [Excel Spreadsheet]

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      Description of Other Relevant Housing Indicators (not mapped)

      Gentrification and Displacement

      Regional development patterns can have a significant impact on the dynamics of gentrification and displacement in particular neighborhoods. And, as the original Equity Atlas (2007) showed, the dynamics of gentrification and displacement play a powerful role in shaping the landscape of regional equity. The displacement of low-income residents and residents of color can lead to decreased community capacity and cohesion, loss of culture, and fractured social support systems. In the Portland metro region, displacement due to gentrification has also moved many low income residents and residents of color to outlying neighborhoods with poorer access to transit, walkable neighborhoods, services, and other opportunities necessary for achieving health and well-being.  The Atlas’ demographic and housing affordability maps provide a visual depiction of the combined effects of gentrification and displacement. But effective methodologies and data do not exist to enable us to isolate and map the patterns and effects of gentrification on their own.

      Fair Housing

      Persons of color, persons with disabilities, and other specific population groups have historically experienced a greater likelihood of unfavorable treatment when attempting to rent, buy, get a mortgage, or secure home insurance. Research has shown that these groups can experience denial, harassment, be given less favorable terms and conditions, or experience a lower level of service than other groups.  Fair housing laws were enacted to protect against illegal housing discrimination based on “protected class status.” These laws prohibit illegal discrimination by landlords, real estate companies, municipalities, banks or other lending institutions, and insurance companies. The only available data on fair housing violations is based on official complaints registered with the government by consumers. However, this complaint data does not lend itself to being mapped because the data only captures cases in which the consumer was aware of the discrimination and was willing to file an official complaint. The number of official complaints most likely reflects only a small percentage of the actual number of cases of housing discrimination, and the sample sizes from the housing complaint data are not large enough to permit accurate mapping.

      Housing Quality

      Housing that exposes residents to toxins, mold, pests, or unhealthy conditions can have an immediate and long-term impact on residents’ health and quality of life. Access to safe and sanitary housing is a key component of equitable access to housing, but this issue could not be mapped as part of the Atlas project because comprehensive data on housing quality is not available for the metro region.

      Homelessness

      The levels of homelessness in a community are a reflection of the extent to which affordable housing, economic opportunity, health and mental health care, and other key resources are widely available and accessible in that community. Each county in the metro area collects comprehensive data on an annual or bi-annual basis on the numbers of people experiencing homelessness on a given night. Some counties disaggregate this data geographically, but most do not. The lack of consistent geographic information, and the variations in how each county collects and reports on its data, made it impossible to map homelessness in a meaningful way for this project. For summary data on the levels of homelessness in each county, see the Greater Portland Pulse Homelessness webpage.

      Regulatory Access

      Local governments use various regulatory tools to shape the housing and land use environment. The presence or absence of codes and regulations that support affordable, high quality, fair, and accessible housing can have a significant impact on whether such housing is likely to exist in a community. An assessment of the codes and regulations in each of the metro area’s jurisdictions would provide insights into whether high quality affordable and fair housing is likely to be available to residents of that jurisdiction now and in the future.  However, comprehensive and consistent data on the regulatory environment within each jurisdiction is not available, and gathering that information was beyond the scope of this project.

      Utility Costs

      Households that spend a significant portion of their incomes on utility costs have less income available to pay for other essential needs. Nationally, low-income households pay about 14% of their income on home energy, which is far above the 3% that higher income families pay. The energy cost burden faced by these households can make it more difficult for them to afford to pay for housing, food, medical care, and other needs. While mapping utility costs would provide a useful addition to the Atlas’ analysis of housing costs, data on utility costs by address is not readily available at a regional level.

      Location of Section 8 Households

      The Atlas includes maps of publicly subsidized housing units, but these units are just one form of publicly-subsidized affordable housing. Section 8 vouchers enable low-income households to rent units in the private market by subsidizing the rent to make it affordable. Data on the locations of individual Section 8 households cannot be mapped due to privacy reasons. Data is available on the distribution of Section 8 households by zip code for Clackamas, Multnomah, and Washington counties for a snapshot in time in 2011. We opted not to map this data because, due to the mobility of Section 8 households, the data would require frequent updates to maintain its accuracy, and such updates are beyond the current capacity of this project. 

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      THEME: PARKS & NATURAL AREAS

       

      Other Relevant Indicators (not mapped)

      • Regional Trails
      • Greenspace Quality and Development
      • Accessible Parks, Trails, and Playgrounds

       


       

      Parks & Natural Areas: Proximity to Parks, Natural Areas, and Greenspaces

      Proximity to Publicly Accessible Parks: Parks are defined as active or passive recreation areas where facilities exist primarily intended for recreational uses by the public; the sitename used by the owner or manager contains the word "Park" (e.g. Washington Park, Oxbow Regional Park, Tom McCall Waterfront Park, etc.).

      Proximity to Publicly Accessible Natural Areas: Natural areas are managed primarily for the value of natural resources as buffers, conservation and/or habitat protection; the sitename used by the owner or manager contains the word "Natural Area" or other conservation designation (e.g. Tryon Creek State Natural Area, Oaks Bottom Wildlife Refuge, etc.).

      Proximity to Greenspaces with Limited Public Access: Greenspaces are a general category that is not specifically a park or natural area; greenspaces generally have limited public access and include common areas of a subdivision or condominium complex, cemeteries, golf courses and school grounds that are not specifically designated for general public use.

      Data Source: Metro RLIS; Clark County GIS

      Data Limitations: Designation of a park, natural area, or greenspace is by general classification only. The mapped layers do not provide information about the type or condition of the facilities or levels of public use. A comprehensive inventory of these attributes would require primary data collection that was not feasible for this project.

      Close geographic proximity to neighborhood parks is an important component of access. For larger regional parks, however, the proximity measure used in the Atlas tool (which is based primarily on walkability) is not as relevant. For this reason, regional parks are included as a reference layer in the Atlas mapping tool rather than an indicator layer.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2012

      Map Classification Scheme: The proximity rasters for parks, natural areas and greenspaces are calculated based on a 1-5 scale using pedestrian proximity to a the street access point to the area. Where access point data was not available, the perimeter of the park is used. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a street access point.
      2 Cells within 3/4 to 1 mile of a street access point.
      3 Cells within 1/2 to 3/4 mile of a street access point.
      4 Cells within 1/4 to 1/2 mile of a street access point.
      5 Cells within 1/4 mile of a street access point.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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      Parks & Natural Areas: Proximity to Recreation Facilities

      Description: Recreation facilities were compiled from the Metro RLIS data and include pools, tennis courts, sports fields, community centers, stadiums, and fairgrounds.

      Data Source: Metro RLIS; Clark County GIS

      Data Limitations:  This data provides a snapshot of key recreational facilities that are publicly accessible, but it is not a comprehensive inventory of all of the recreation facilities in the region. In particular, it does not include privately-owned recreation facilities such as private membership gyms, sports clubs, and pools.

      Geographic proximity to recreation facilities does not necessarily translate into access. For example, having a community center in the neighborhood does not reflect access if the programs offered at the community center cost too much or are not culturally appropriate. However, data on programming and usage of recreation facilities was not available for mapping.

      In the RLIS database, sports fields are coded in the same way as stadiums and fairgrounds, which is why fairgrounds are included in the map.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2012

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a the street access point to the area. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a street access point.
      2 Cells within 3/4 to 1 mile of a street access point.
      3 Cells within 1/2 to 3/4 mile of a street access point.
      4 Cells within 1/4 to 1/2 mile of a street access point.
      5 Cells within 1/4 mile of a street access point.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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      Parks & Natural Areas: Proximity to Water Access Points

      Description: The Water Access indicator shows proximity to points where motorized and non-motorized boats can be launched. These sites have parking areas for cars and include boat ramps managed by both public agencies and private organizations.

      Data Source: Oregon Counties (Oregon Geospatial Enterprise Office); Clark County (Washington State Recreation and Conservation Office)

      Data Limitations: The datasets for Oregon and Washington are fairly old, but represent the most complete dataset publicly available. A more recent compilation of boat launch sites would require primary data collection that was not feasible for this project.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 1989 (OR); 2003 (WA)

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a the boat launch access point. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from the access point.
      2 Cells within 3/4 to 1 mile of the access point.
      3 Cells within 1/2 to 3/4 mile of the access point.
      4 Cells within 1/4 to 1/2 mile of the access point.
      5 Cells within 1/4 mile of the access point.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the data source links above to access more detailed information.

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      Description of Other Relevant Parks & Natural Areas Indicators (not mapped)

      Regional Trails

      Proximity to regional trails is an important component of the broader issue of access to parks and nature. Walking trails provide opportunities for recreation, exercise, and exposure to nature. Unfortunately, RLIS data on the region’s walking trails does not include trail entry points, so it was not possible to map this indicator in a meaningful way.

      Greenspace Quality and Development

      The Atlas maps measure proximity to publicly accessible parks and natural areas, but they do not provide any information about the quality of those parks and natural areas. While proximity to greenspace of any kind is beneficial, the benefits increase if the greenspace has been developed to offer amenities and recreational opportunities such as playgrounds, restrooms, basketball courts, ball fields, etc.  Unfortunately, the available information on greenspace quality and development is not up-to-date or comprehensive enough to enable us to map this issue in a consistent way at a regional scale.

      Accessible Parks, Trails, and Playgrounds

      Access to parks and natural areas is not truly equitable unless those areas are physically accessible by all adults and children, regardless of physical ability or mobility. Some parks, trails, and playgrounds in the region are designed to be truly accessible to all users, but these tend to be the exception rather than the norm. Unfortunately, comprehensive data is not available at a regional scale to enable us to map this issue.

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      THEME: SERVICES & AMENITIES

       

      Other Relevant Indicators (not mapped)

      • Sub-prime Financial Services
      • Broadband Infrastructure
      • Emergency Services
      • Culturally Appropriate Services
      • Service Affordability
      • Proximity to Tobacco Retailers

       


       

      Services & Amenities: Proximity to Financial Services

      Description: The Financial Services indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes commercial banking (522110), Savings Institutions (522120), and Credit Unions (522130).

      Data Source: ESRI Business Analyst

      Data Limitations: NAICS codes are self-reported and thus represent what the business deems its primary service. Also, these data sources do not capture the full range of financial services available across the region. They merely represent the types of institutions for which comprehensive data is available. Mapping all the financial services in every neighborhood across the region would require primary data collection at a scale that was not feasible for this project.

      Geographic proximity to financial service institutions does not necessarily translate into access. Mapping access to financial services in a more comprehensive way is not possible given the available data, but the maps in the Atlas that look at access to home mortgage lending offer some insights into this important issue (see Housing indicators).

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2010

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a street.
      2 Cells within 3/4 to 1 mile of a street.
      3 Cells within 1/2 to 3/4 mile of a street.
      4 Cells within 1/4 to 1/2 mile of a street.
      5 Cells within 1/4 mile of a street.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations and institutions.

      Link to Data [Excel Spreadsheet]

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      Services & Amenities: Proximity to Key Retail Services

      Description: The Key Retail Services indicator is compiled from a list of NAICS codes (North American Industry Classification System). The industries included in the indicator were chosen based on an index created by the Healthy Development Measurement Tool.

      • General Automotive Repair (811111)
      • Barber & Beauty Shops (812111)
      • Beauty Salons (812112)
      • Sporting Goods Stores (451110)
      • Laundries & Dry Cleaners (812310)
      • Drycleaning & Laundry Services (812320)
      • Fitness & Recreational Sports Centers (713940)
      • Hardware Stores (444130)
      • Pharmacies & Drug Stores (446110)
      • Motion Picture Theaters (512131)
      • Drive-In Motion Picture Theaters (512132)
      • Video Tape & Disk Rental (532230)

      Data Source: ESRI Business Analyst

      Data Limitations: NAICS codes are self-reported and thus represent what the business deems its primary service. Also, these data sources do not capture the full range of retail services available across the region. They merely represent the types of businesses for which comprehensive data is available. Mapping all the retail services in every neighborhood across the region would require primary data collection at a scale that was not feasible for this project.

      The definition of what constitutes a “Key Retail Service” is subjective. Given this subjectivity, we chose to rely on the definition developed by the Healthy Development Measurement Tool (HDMT), a highly regarded indicators project. HDMT developed this index based on extensive research [see link above]. Nonetheless, we recognize that proximity to drycleaners or fitness centers may be irrelevant to some residents, while access to other services not included in this measure may be very important. For this reason, it is important to clarify the specific services represented by this  indicator before drawing any conclusions about retail access based on this indicator.

      Geographic proximity to retail services does not necessarily translate into access. This indicator does not provide any information on other key components of access such as cost, cultural appropriateness, or hours of operation. Such data is not available to the public in a comprehensive way and therefore cannot be mapped.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2010

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a street.
      2 Cells within 3/4 to 1 mile of a street.
      3 Cells within 1/2 to 3/4 mile of a street.
      4 Cells within 1/4 to 1/2 mile of a street.
      5 Cells within 1/4 mile of a street.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations and institutions.

      Link to Data [Excel Spreadsheet]

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      Services & Amenities: Proximity to Public Services

      Description: The Public Services indicator is compiled from point data in the Metro RLIS dataset (city halls, fire stations, hospitals) supplemented by a list of NAICS codes (North American Industry Classification System) that includes Courts (922110), Police Protection (922120), Fire Protection (922160), Government Executive Offices (921110), and Postal Service (491110). Duplicates have been removed from the mapped dataset.

      Data Source: ESRI Business Analyst, Metro RLIS

      Data Limitations: NAICS codes are self-reported and thus represent what the business deems its primary service. Also, these data sources do not capture the full range of public services available across the region. They merely represent the types of institutions for which comprehensive data is available. Mapping all the public services in every neighborhood across the region would require primary data collection at a scale that was not feasible for this project.

      Geographic proximity to public services does not necessarily translate into access. This indicator does not provide any information on other key components of access cultural appropriateness or hours of operation. Such data is not available to the public in a comprehensive way and therefore cannot be mapped.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2010 (Business Analyst); 2012 (RLIS)

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a street.
      2 Cells within 3/4 to 1 mile of a street.
      3 Cells within 1/2 to 3/4 mile of a street.
      4 Cells within 1/4 to 1/2 mile of a street.
      5 Cells within 1/4 mile of a street.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations and institutions.

      Link to Data [Excel Spreadsheet]

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      Services & Amenities: Proximity to Human and Social Services

      Description: The Human and Social Services indicator is compiled from a list of NAICS codes (North American Industry Classification System) that includes Individual and Family Services (624190), Child and Youth Services (624110), Services for Elderly and Persons with Disabilities (624120), Temporary Shelters (624221), and Other Community Housing Services (624229).

      Data Source: ESRI Business Analyst

      Data Limitations: NAICS codes are self-reported and thus represent what the business deems its primary service. Also, these data sources do not capture the full range of human and social services available across the region. They merely represent the types of institutions for which comprehensive data is available. Mapping all the human and social services in every neighborhood across the region would require primary data collection at a scale that was not feasible for this project.

      Geographic proximity to human and social services does not necessarily translate into access. This indicator does not provide any information on other key components of access cultural appropriateness or hours of operation. Such data is not available to the public in a comprehensive way and therefore cannot be mapped.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2010

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using pedestrian proximity to a street network. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a street.
      2 Cells within 3/4 to 1 mile of a street.
      3 Cells within 1/2 to 3/4 mile of a street.
      4 Cells within 1/4 to 1/2 mile of a street.
      5 Cells within 1/4 mile of a street.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers. See the link below [Link to Data] to download an Excel spreadsheet for the full dataset that includes name, address, city, state, zip and NAICS codes of the selected businesses, organizations and institutions.

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      Description of Other Relevant Services & Amenities Indicators (not mapped)

      Sub-prime Financial Services

      Many low-income households lack access to bank accounts and, as a result, they pay high costs for basic financial transactions. Pay day loan and check cashing businesses provide needed services, but they do so with exorbitant fees and interest rates that impose additional financial burdens on low-income households. Mapping the locations of sub-prime financial services, and how these location patterns correlate with neighborhood demographics, would be a valuable addition to the Atlas’ maps on access to financial institutions. However, comprehensive data on the locations of check cashing and pay day loan businesses is not available in a form that would enable us to map this indicator.

      Broadband Infrastructure

      Access to the internet has become an essential pre-requisite for engagement in the broader economy. But some neighborhoods still lack basic access to broadband infrastructure. Some stakeholders were interested in including maps of broadband infrastructure in the Atlas as a way of measuring equitable access to information technology. The necessary data was not available to enable us to map this issue, but even if it had been, interpreting the data would have been difficult.  Access to broadband infrastructure is irrelevant if a household can’t afford to pay for the equipment and monthly service fees necessary to take advantage of the infrastructure. For this reason, a better measure might have been household access to information technology; unfortunately, comprehensive data is not available for that measure at a neighborhood level.

      Emergency Services

      In many emergencies, the speed of response times for ambulances, fire trucks, and police can make a life or death difference. Particularly in rural areas, response times can vary significantly from neighborhood to neighborhood. Mapping inequities in response times could provide valuable information to inform emergency services planning. However, while data on response times is collected by each individual responding agency within each jurisdiction, there is no comprehensive data collection or reporting across the individual agencies. Gathering the data and attempting to make it uniform across agencies so that it could be effectively mapped at a regional scale was beyond the capacity and scope of this project.

      Culturally Appropriate Services

      Geographic proximity to retail services and other community amenities is irrelevant if those services do not meet the specific needs of individual households. For many households, services need to be culturally-specific in order to effectively meet that household’s needs. While the availability of culturally-specific services is therefore an important equity issue, comprehensive data is not available that would enable us to map this issue.

      Service Affordability

      Geographic proximity to retail services is not relevant if those services are not affordable to local residents.  Mapping the affordability of retail services would therefore provide a valuable addition to the Atlas’ maps on access to services and amenities. Unfortunately, comprehensive data on businesses’ prices or service affordability is not available to the public.

      Proximity to Tobacco Retailers

      Tobacco use, particularly among youth is a key contributor to poor health outcomes. Research has shown that the proximity to tobacco retailers is correlated with youth tobacco use. Research has also shown that tobacco industry advertising and promotional activities – most of which are focused on the retail establishments where tobacco is sold – have a strong influence on the onset and continuation of smoking by adolescents and young adults. For these reasons, health advocates view the location of tobacco retailers as a key factor affecting the prevalence of tobacco use. Mapping tobacco retailers for the four-county region was beyond the current capacity of the Atlas project but this indicator may be mappable in later iterations of the project.

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      THEME: TRANSPORTATION

       

      Other Relevant Indicators (not mapped)

      • Connectivity
      • Public Transit Quality and Safety
      • Transit Rider Demographics
      • Crosswalks and Curb Cuts
         

       

      Transportation: Transit Access

      Description: The Transit Access indicator is a measure of the proximity to public transit stops and the frequency of trips through those transit stops (bus, streetcar, MAX and Vancouver transit). For example, a bus stop that serves two high-frequency bus lines will have a higher weighting than a stop that serves a single, more limited frequency line.

      Data Source: Metro RLIS and Clark County GIS

      Data Limitations: While this indicator measures the frequency of trips through transit stops, it does not measure connectivity -- i.e. how easy it is to get from one place to another via the transit lines that are available at a given transit stop. Connectivity is a key component of transit access, but mapping connectivity of transit lines in a comprehensive way was not possible within the scope of this project.

      The transit data for this measure do not include several locally run rural bus lines that serve communities that are not served by other public transit options.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon); Clark County (Washington)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2012

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using point proximity to a street network. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a stop.
      2 Cells within 3/4 to 1 mile of a stop.
      3 Cells within 1/2 to 3/4 mile of a stop.
      4 Cells within 1/4 to 1/2 mile of a stop.
      5 Cells within 1/4 mile of a stop.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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      Transportation: Walkability (sidewalk density)

      Description: The Walkability indicator shows the density of sidewalk coverage as a measure of the walkability of a particular area. A 1/4 mile kernel density search radius is used in the Walkability raster layer as this is a generally accepted walking distance.

      Data Source: Metro RLIS

      Data Limitations: The presence of sidewalks in only one component of walkability. The data layers do not provide any detail about the condition of the sidewalk or whether there are any impediments (such as low hanging tree branches or lack of curbcuts). They also do not provide any indication of traffic volume, the presence of crosswalks, and other factors that facilitate pedestrian access.

      Sidewalk data is often not completely up to date because the information changes on an ongoing basis. The accuracy of sidewalk data varies. The data for the city of Portland is generally quite accurate, but is less accurate for areas outside of Portland and is non-existent for many rural areas. Care should be taken in interpreting sidewalk coverage in outlying areas as accuracy is severely diminished. The City of Vancouver, in Clark County, is currently compiling updated data on sidewalk coverage, but this data was not available for this iteration of the mapping tool. For this reason, sidewalk data is not included for Clark County.

      Geographic Extent: Oregon Only (Multnomah, Clackamas and Washington Counties)

      Geographic Unit: Density Raster (264' cell size)

      Date of Data: 2012

      Map Classification Scheme (Density): Density rasters are displayed using a 1-5 classification scheme. Blues represent low density. Browns represent high density.

      Rank
      Description
      1 Low
      2 Medium Low
      3 Medium
      4 Medium High
      5 High

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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      Transportation: Bikeability

      Description: The Bikeability indicator is a density raster that shows suitability for biking and is based on Metro's "Bike There!" map designations. Cells in the raster were weighted based on the suitability classifications (good, moderate and less suitable). This map shows a more diffuse pattern than Walkability because a 1 mile kernel density was used as a search radius due to the added mobility of bikes (a 1/4 mile kernel density is used in the Walkability raster layer).

      Bike There! Designations:

      • Good for Biking (bike lane, low traffic, low speed)
      • Moderately Suitable for Biking (busy streets with bike lane and speeds generally greater than 25 mpg)
      • Less Suitable for Biking (high traffic, speeds greater than 35 mpg, sharp curves and/or narrow lanes)

      Data Source: Metro

      Data Limitations: There are two main limitations to this indicator. Connectivity is not taken into account.  A grid will have more connectivity than a curvilinear street pattern with cul-de-sacs. However, the current raster does not account for this and would rate curvilinear streets just as high as gridded streets. In addition, the street designations on the map were also influenced by local interpretations.  If designations differ from one city to the next, comparisons might not be equal.  For instance, within the city of Portland, there are many “low traffic” through-streets that do not get a high designation on the Bike There! map, whereas many of the low traffic through streets in Tigard tend to get a high designation, increasing the density of areas coded as “good bike suitability” in Tigard.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon); Clark County (Washington)

      Geographic Unit: Density Raster (264' cell size)

      Date of Data: 2012

      Map Classification Scheme (Density): Density rasters are displayed using a 1-5 classification scheme. Blues represent low density. Browns represent high density.

      Rank
      Description
      1 Low
      2 Medium Low
      3 Medium
      4 Medium High
      5 High

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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      Transportation: Mobility Access (para-transit LIFT requests and ramp deployments)

      Description: The Mobility Access indicator shows the density of para-transit LIFT requests and bus/train ramp deployments. The maps are created from GTFS (General Transit Feed Specification) data collected by TriMet. GTFS is a common format used to document public transportation schedules and associated geographic information. The master data file contains information about ramp deployments (where a rider requests that a bus or train ramp is deployed to allow for wheelchair access). Data is also provided for para-transit LIFT service by pick-up location (special transit vehicles by reservation only). LIFT service is available to all ADA certified passengers.

      Data Source: TriMet (GTFS master file)

      Data Limitations: Because para-transit usage is a request-based service, the patterns shown on the map do not necessarily reflect inequitable access. They may reflect lower transit usage in general in certain parts of the region. Or, they may reflect less awareness of the availability of para-transit in certain parts of the region.

      The data for this indicator come from TriMet and do not include other public transit providers in the region that may offer para-transit services.

      Geographic Extent: Oregon Only (Multnomah, Clackamas and Washington Counties)

      Geographic Unit: Proximity Raster (264' cell size)

      Date of Data: 2012

      Map Classification Scheme: Proximity rasters are calculated based on a 1-5 scale using point proximity to a street network. Blues represent large distances. Browns represent short distances.

      Rank
      Description
      1 Cells greater than 1 mile from a street.
      2 Cells within 3/4 to 1 mile of a street.
      3 Cells within 1/2 to 3/4 mile of a street.
      4 Cells within 1/4 to 1/2 mile of a street.
      5 Cells within 1/4 mile of a street.

      Data Table Field Headings: Summary tables with limited attributes for selected geographic areas are available for download in the online Atlas mapping tool for raster layers.

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      Transportation: Percent of Households with No Motorized Vehicle

      Description: The Percent of Households with No Motorized Vehicle indicator shows the percent of households that indicated they have no car (no personal motorized mode of transportation). Company or government vehicles kept at a residence do not constitute a vehicle as they are not generally for personal use.

      Data Source: American Community Survey (ACS); DP04 Selected Economic Characteristics

      Data Limitations: Because of sample size issues, the margins of error tends to be quite high when disaggregating ACS data. Consequently, this indicator is mapped at the PUMA level -- a relatively coarse geographic unit, but one where the margin of errors are at an acceptable level. The maps can be used to discern general regional patterns only.

      The attribute table contains information on the margins of error and should be consulted before using this data for any analyses. Data can be downloaded using the link below.

      The dataset does not distinguish between those who choose not to own an automobile versus those who are financially unable to purchase an automobile or are unable to for other reasons (e.g. disability).

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: PUMA 2010

      Date of Data: ACS 5-year (2006-2010)

      Map Classification Scheme:

      Class/Values Description
      2% - 4% Percent of households that do not have a motorized vehicle for personal use.
      5% - 10% Percent of households that do not have a motorized vehicle for personal use.
      11% - 21% Percent of households that do not have a motorized vehicle for personal use.

      Data Table Field Headings:

      Heading Description
      PUMA PUMA ID
      PNoVeh Percent of households with no personal motorized vehicle.
      PNoVehMOE Margin of error for the percent of households with no personal motorized vehicle.

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      Transportation: Average Commute Time to Work (in minutes)

      Description: The Average Commute Time to Work indicator shows the average amount of time (in minutes) that it takes an individual to travel to work. Commute time refers to the total number of minutes that it customarily takes the individual to get to work including time spent waiting for public transportation, picking up passengers for a carpool, and any other activities (such as dropping children off at school or daycare).

      Data Source: American Community Survey (ACS); DP04 Selected Economic Characteristics

      Data Limitations: Because of sample size issues, the margin of error tends to be quite high when disaggregating ACS data. Consequently, this indicator is mapped at the PUMA level -- a relatively coarse geographic unit, but one where the margins of error are at an acceptable level. The maps can be used to discern general regional patterns only.

      The attribute table contains information on the margins of error and should be consulted before using this data for any analyses. Data can be downloaded using the link below.

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: PUMA 2010

      Date of Data: ACS 5-year (2006-2010)

      Map Classification Scheme:

      Class/Values Description
      18.8 - 23.2 Average commute time (in minutes).
      23.21 - 26.1 Average commute time (in minutes).
      26.11 - 31.5 Average commute time (in minutes).

      Data Table Field Headings:

      Heading Description
      PUMA PUMA ID
      TravelTime Commute time in minutes.
      TimeMOE Margin of error for commute time in minutes.

      Link to Data [Excel Spreadsheet]

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      Transportation: Mode of Commute to Work

      • Commute by Car
      • Commute by Public Transit
      • Commute by Walking
      • Commute by Other Means (any mode not car, public transit or walking, including biking)

      Description: The Mode of Transit indicators show the percent of the working population (16 years and older) by the principle means of transportation to work. People who used different means of transportation on different days of the week were asked to specify the one they used most often (the greatest number of days).

      Data Source: American Community Survey (ACS); DP04 Selected Economic Characteristics

      Data Limitations: Commute by Other Means includes any mode of transportation to work not by car, public transit or walking. Other means therefore includes biking (as long as it is deemed the primary means of transportation). Biking as a primary mode of transportation to work cannot be disaggregated from this category.

      Because of sample size issues, the margins of error tend to be quite high when disaggregating ACS data. Consequently, these indicators are mapped at the PUMA level -- a relatively coarse geographic unit, but one where the margins of error are at an acceptable level. The maps can be used to discern general regional patterns only.

      The attribute table contains information on the margins of error and should be consulted before using this data for any analyses. Data can be downloaded using the link below.

      The dataset does not provide distinction between persons who customarily use multiple modes of transit -- such as driving a distance to a commuter train or ferry. Persons are asked to choose the mode of transit that constitutes the primary mode (in number and time spent). For this reason, the data may under-represent modes of transportation such as biking and walking, which may be used as an alternative to the primary mode or which may be a component of a multi-modal commuting strategy. Similarly, because the data only focus on transportation for commuting, they do not capture information on the use of alternative modes of transportation such as biking and walking for non-work transportation. And, because the survey question asks respondents only about their primary mode of transportation [from the previous week], it does not capture variations based on weather or time of year, which may result in further under-reporting of active transportation modes.

      For an example of local data on transportation modes that more effectively capture both work-related and non-work related transportation, see the City of Portland's "Annual Community Survey Results Report."

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: PUMA 2010

      Date of Data: ACS 5-year (2006-2010)

      Map Classification Scheme: Commute by Car

      Class/Values Description
      55.1% - 61.4% Percent of working population that commute primarily by car.
      61.41% - 73% Percent of working population that commute primarily by car.
      73.01% - 78.5% Percent of working population that commute primarily by car.

      Data Table Field Headings: Commute by Car

      Heading Description
      PUMA PUMA ID.
      CommuteCar Count of working population that commutes primarily by car.
      CarMOE Margin of error for the count of working population that commutes primarily by car.
      PCar Percent of working population that commutes primarily by car.
      PCarMOE Margin of error for the percent of working population that commutes primarily by car.

      Map Classification Scheme: Commute by Public Transportation

      Class/Values Description
      0% - 4% Percent of working population that commute primarily by public transportation.
      5% - 9% Percent of working population that commute primarily by public transportation.
      10% - 14% Percent of working population that commute primarily by public transportation.

      Data Table Field Headings: Commute by Public Transportation

      Heading Description
      PUMA PUMA ID.
      Public Count of working population that commutes primarily by public transportation.
      PublicMOE Margin of error for count of working population that commutes primarily by public transportation.
      Ppublic Percent of working population that commutes primarily by public transportation.
      PCarMOE Margin of error for the percent of working population that commutes primarily by public transportation.

      Map Classification Scheme: Commute by Walking

      Class/Values Description
      1% - 3% Percent of working population that commute primarily by walking.
      4% - 6% Percent of working population that commute primarily by walking.
      7% - 11% Percent of working population that commute primarily by walking.

      Data Table Field Headings: Commute by Walking

      Heading Description
      PUMA PUMA ID.
      Walk Count of working population that commutes primarily by walking.
      WalkMOE Margin of error for the count of working population that commutes primarily by walking.
      PWalk Percent of working population that commutes primarily by walking.
      PWalkMOE Margin of error for the percent of working population that commutes primarily by walking.

      Map Classification Scheme: Commute by Other Means (including biking)

      Class/Values Description
      1% - 2% Percent of working population that commute primarily by other means.
      3% - 4% Percent of working population that commute primarily by other means.
      5% - 10% Percent of working population that commute primarily by other means.

      Data Table Field Headings: Commute by Other Means (including biking)

      Heading Description
      PUMA PUMA ID.
      Other Count of working population that commutes primarily by other means.
      OtherMOE Margin of error for the count of working population that commutes primarily by other means.
      Pother Percent of working population that commutes primarily by other means.
      POtherMOE Margin of error for the percent of working population that commutes primarily by other means.

      Link to Data [Excel Spreadsheet]

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      Transportation: Public Transit Stop Safety Amenities

      • Curbcuts
      • Sidewalks

      Description: The Public Transit Stop Safety Amenities indicators show the bus, streetcar, and MAX stops that contain safety amenities such as curbcuts and sidewalks. These two amenities are mapped separately. Overlaying the two point data layers can be used to identify stops with both amenities.

      Data Source: TriMet (GTFS Master File)

      Data Limitations: This indicator only shows TriMet transit stops; comparable data for other public transit operators in the region were not available.

      The GTFS Master File contains data on a number of additional safety amenities (such as street lighting, crosswalks, and shelters). Time constraints prevented adding these additional layers. Curbcuts and sidewalks were deemed most important for accessibility to transit (for those with mobility issues, in particular).

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Single Points

      Date of Data: 2012

      Map Classification Scheme: Transit Stops with Curbcuts and/or Sidewalks

      Class/Values Description
      Bus Stop Indicates an amenity located at a bus stop.
      Streetcar Indicates an amenity located at a streetcar stop.
      MAX Indicates an amenity located at a MAX stop.
      Bus & Streetcar Indicates an amenity located at a combined bus/streetcar stop.

      Data Table Field Headings: Transit Stop with Curbcuts and/or Sidewalks

      Heading Description
      STOP_NAME Transit stop intersection.
      JURISDIC City where the transit stop is located.
      TYPE Type of transit (bus, streetcar, MAX or bus/streetcar)

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      Transportation: Transportation Safety (ODOT Crash Data -- OR Only)

      • ODOT Crash Data -- Fatalities
      • ODOT Crash Data -- Car-Car Incidents
      • ODOT Crash Data -- Car-Pedestrian Incidents
      • ODOT Crash Data -- Car-Bike Incidents

      Description: The Public Transportation Safety indicators show the locations of transportation accidents and fatalities. The ODOT Crash Analysis and Reporting (CAR) Unit compiles crash data from individual driver and police crash reports submitted to the Department of Motor Vehicles (DMV) as required by Oregon state law.

      For ease in using the data layers (as they contain numerous point features), the Car-Car, Car-Pedestrian and Car-Bike incidents are displayed using separate layers (these are incidents that did not result in a fatality). The classification scheme for the Fatalities layers indicates whether the incident involved a Car-Car, Car-Pedestrian, or Car-Bicycle.

      Data Source: Oregon Department of Transportation (ODOT); Crash Analysis and Reporting Unit

      Data Limitations: The state of Oregon has set threshold limits for crash reporting based on estimated property damage and personal injury.
      Oregon law currently requires that any crash on a public roadway resulting in a fatality, bodily
      injury or damage to one person's property in excess of $1,000 must be reported to the DMV. Submittal of these crash reports are the responsibility of the individual, which likely results in undercounting. Approximately 33% of all reported crashes are also investigated by a police officer, who also files a report to the DMV.

      In the Fatalities layer, detail is not provided on who (e.g. the pedestrian, bicyclist or driver) or how many fatalities occurred. Those interested in further details about specific incidents should refer to the ODOT CAR website:

      [Link to Oregon Department of Transportation Crash Analysis and Reporting Unit]

      Geographic Extent: Multnomah, Clackamas and Washington Counties (Oregon) and Clark County (Washington)

      Geographic Unit: Single Points

      Date of Data: 2011

      Map Classification Scheme: Fatalities

      Class/Values Description
      Car - Pedestrian Indicates a fatality that occurred in an incident involving a car and a pedestrian.
      Car - Car Indicates a fatality that occurred in an incident involving two or more cars.
      Car - Bicycle Indicates a fatality that occurred in an incident involving a car and a bicycle.

      Map Classification Scheme: Car-Car, Car-Pedestrian and Car-Bicycle Incidents

      A single point symbol is used for the incident locations that did not result in a fatality.

      Data Table Field Headings: No detailed information about the incident is included in these layers.

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      Description of Other Relevant Transportation Indicators (not mapped)

      Connectivity

      The geographic proximity of a given location to transit lines, streets, sidewalks, and bike paths is not an effective measure of transportation access unless those modes of transportation actually enable users to get where they need to go.  “Connectivity” measures how well a neighborhood’s transit lines, streets, sidewalks, and bike paths connect to one another, and therefore how quickly and efficiently people can travel to a range of destinations using different modes of transportation. Measuring connectivity also enables us to assess how easily the residents of a given neighborhood can access all of the other resources needed for daily life.  Unfortunately, even though connectivity is an important component of transportation equity, developing a methodology for mapping connectivity and gathering the necessary data were beyond the capacity of this project.

      Public Transit Quality and Safety

      The quality of public transit service is an important transit equity issue. This includes the reliability of transit lines, the quality of transit stops (such as the presence of shelters, benches, sidewalks, and lighting), and rider safety.  Lack of reliable, safe public transit can have an adverse impact on people who rely on public transit for their travel needs. Perceptions of poor transit quality or lack of safety can also reduce ridership rates and undermine overall public support for transit. The Atlas includes some maps related to this issue, namely the presence of sidewalks and curb cuts at public transit stops. But data was not available to enable us to map all of the dimensions of this issue in a comprehensive way.

      Transit Rider Demographics

      Geographic data on the demographics and socio-economic status of transit riders would be a valuable addition to the Atlas’ transit access maps. Such data could help to inform efforts to make transit planning more equitable. For example, understanding the income composition of the ridership of each of TriMet’s bus lines could help to inform more equitable planning when decisions need to be made about adding or reducing capacity on specific lines. However, comprehensive data on transit user demographics is not available in a form that would enable us to map this information.

      Crosswalks and Curb Cuts

      The Atlas uses sidewalk access as a proxy for walkability. While sidewalks are certainly an important pre-requisite for walkability, the presence of crosswalks and curb cuts, as well as the quality of the sidewalks, can have an important impact on walkability. Without crosswalks, some intersections can be daunting (and dangerous) for walkers. Without curb cuts, sidewalks are rendered unusable for people in wheelchairs, people pushing strollers or carts, or people with limited mobility. Similarly, poor quality sidewalks can pose obstacles for people in wheelchairs or with limited mobility. While Metro and other jurisdictional partners recognize the value of this data, comprehensive data on crosswalks, curb cuts, or sidewalk quality is currently not available at a regional scale.

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