Tag Archives: census tract demographics

Examining Health Characteristics by Census Tract

.. new data, new ways to examine health characteristics at the city and census tract/subcounty level.  For example, among the 500 largest U.S. cities in 2014, the incidence of high blood pressure ranged from 22.5% (Longmont, CO) to 47.8% (Gary, IN). Use the interactive table to view, rank, compare this and other new wide-ranging health statistics for the 500 largest U.S. cities and associated census tracts. See the related Web section for more detail.

At the census tract/neighborhood level, 937 tracts have more than 10% of the population ages 18 years and over with coronary heart disease. What are characteristics of health-related factors in your city, neighborhood and census tracts of interest? Use tools reviewed in this section to access/analyze a wide range of health-related characteristics (see items list below) — not available at the city or census tract level before.

Patterns of High Blood Pressure: Honolulu, HI by Census Tract
This graphic illustrates visual analysis and analytical potential for tracts in cities covered.

– Click graphic for larger view with high blood pressure %population label
– View developed with CV XE GIS software and related GIS project/fileset.

Accsss/analyze these data for approximately 28,000 tracts (of a total approximate 74,000) on topics including chronic disease risk factors, health outcomes and clinical preventive service use for the largest 500 cities in the U.S. These small area data enable stakeholders in cities, local health departments, neighborhoods and study areas to better understand the characteristics and geographic distribution of health-related measures and how they might impact health-related programs and other demographic-economic issues.

Scope of 500 Cities
The following graphic shows the 500 cities (green areas) included in project. Data for these cities and intersecting tracts are available. Click graphic for larger view providing county visibility and city name labels. Expand browser to full window for best quality view.

– View developed with CV XE GIS software and related GIS project/fileset.

The 500 Cities data have been developed as a part of the CDC 500 Cities project, a collaboration between the Centers for Disease Control (CDC), the Robert Wood Johnson Foundation and the CDC Foundation. These data are being integrated into the Situation & Outlook (S&O) database and included in the S&O metro reports. Examine health-related characteristics of metro cities and drill-down areas in combination with other demographic-economic measures.

Analytical Potential
These data provide only the health characteristics attributes. They are a small, but important, subset of a larger set of key health metrics. These data are estimates subject to errors of estimation and provide a snapshot view of one point in time.

The value of these data can be leveraged by linking them with other demographic-economic data from the American Community Survey (ACS 2015) tract and city data. Integrate and analyze these data with related data and alternative geography. See related health data analytics section.

Patterns of Heart Disease; Charlotte, NC-SC Area by Tract
This graphic illustrates coronary heart disease patterns by census tract for cities included in the database. Gray areas are census tracts not included in the 500 cities database. Click graphic for larger view.
– View developed with CV XE GIS software and related GIS project/fileset.

Using the Interactive Table
Use the interactive table to view, rank, compare, query these health measures by city. The following graphic illustrates how the table can be used to examine patterns of Texas cities. Table operations are used to selected Texas cities then rank the cities based on the “Access” column — “Current lack of health insurance among adults aged 18-64 Years”.

Try it yourself. Use the table to examine a set of cities in a state of interest.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Importance of Census Tracts in Data Analytics

census tracts are important for many reasons. It is easy to misidentify or misunderstand patterns and characteristics within cities, counties and metros which become obfuscated using these higher level, more aggregate, geographies. Many cities and counties that might be experiencing demographic-economic decline will often have bright spots that are groups of a few or many census tracts.

Patterns of Percent Population with Bachelor’s Degree
— by Census Tract; Los Angeles Metro
The following graphic shows percent population age 25 years and over with bachelor’s degree by census tract based on ACS 2014 5 year estimates for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals. This map illustrates the geographic level of detail available using census tract demographics and the relative ease to gain insights using geospatial data analytics tools.

– View developed using CV XE GIS and related GIS project.

Get a Custom Map for Your Area of Interest
Use this form to request a no fee map graphic similar to the one shown above for a county of interest. Enter the request with county name and state in the text section; e.g., “Requesting social characteristics tract map for Cook County, IL.”

This section reviews reasons for the importance of census tracts in data analyyics. See related Web sections on tools, resources and methods that you can use to access, integrate and analyze U.S. by census tract general demographics data. The U.S. national scope Census Tracts Demographic-Economic Dataset contains approximately 600 subject matter items tabulated for each census tract organized into four subject matter groups:
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

Importance of Census Tracts for Data Analytics
Census tracts are important for many reasons.  A partial list of reasons is provided below.
• Covering the U.S. wall-to-wall, census tracts are the preferred “small area” geography for superior data analytics.
• The Census Bureau now produces annual tract demographic-economic data from the American Community Survey;  there is an evolving time-series at the tract level creating new analytical opportunities.
• Originally developed to equivalence neighborhoods, many still do.
• Defined by the Census Bureau in collaboration with local groups, tracts typically reflect boundaries meaningful for local area analysis.
• Defined generally for use with each new decennial census, most tract boundaries are stable and non-changing for ten years and many much longer.
• Designed to average 4,000 population, there are more than twice as many census tracts (73,056) than ZIP code areas (33,129).
• Tract boundaries are well-defined; unlike ZIP code areas which are subject to multi-sourced geographic definitions.
• Many data developers (e.g., epidemiologists) use census tract geography to tabulate their own small area data enabling more effective use of those data with Census Bureau census tract data.
• As a statistical geographic area (in contrast to politically defined areas, census tracts are coterminous with counties; data at the census tract level can be aggregated to the county level.
• Small area estimates for tracts are typically more reliable than for block groups.
.. census tracts are comprised on one or more coterminous block groups.
.. on average, a census tract is comprised of three block groups.
• Census tracts are used by many Federal, state and local governments for compliance and program management.

The annually updated American Community Survey provides “richer” demographic-economic characteristics for national scope census tracts. While Census 2010 provides data similar to those items in the General Demographics section, only ACS sourced data provide details on topics such as income and poverty, labor force and employment, housing value and costs, educational participation and attainment, language spoken at home, among many related items. The approximate 600 items accessible via the tract dataset are supplemented by a wide range of additional subject matter. ACS census tract data are updated annually in December of each year.

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about using census tract geography and demographic-economic data.  Learn more about integrating these data with other geography, your data and use of data analytics that apply to your situation.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

K-12 Data Analytics: Dallas ISD, Texas

.. using tools and data analytics methods for analysis of K-12 schools located in Dallas ISD school district, Texas .. use the interactive table in related section to examine demographic-economic characteristics of Dallas County by block group. Apply these tools and methods to your schools, school districts and related areas of interest. Contact me for details. Tools and methods described here can help leadership, staff and stakeholders answer key questions and facilitate strategic planning. See the related main Web section for more details and tools access.

Examining the Current Situation
While most schools and school districts know a lot about the students, often less is known about children’s living environment and the broader school district community. See the demographic-economic profile for Dallas ISD total population (compare to Dallas city). These profiles tell a story. It helps stakeholders know “where we are now.”

Use the annually updated School District Special Tabulation that provides similar data but for the grade relevant school age population by type of enrollment universe. See Dallas ISD Children’s Demographic-Economic Profile by Universe of Enrollment.

Dallas ISD School District in Context
Dallas ISD (bold brown boundary) shown in regional context.

  — view created using CV XE GIS and associated GIS Project

School Locations in Context
Zoom-in to Dallas ISD. Pointer at county boundary; Dallas ISD is located in Dallas County. Schools are shown by different types of markers. See markers/style in legend at left. Using the query feature, it is possible to identify charter schools as one type of marker, irrespective of grade range.

Use the national scope interactive tables to examine characteristics of individual public schools and individual private schools. Rank, query, compare and contrast schools within a state or on a national basis.


  — view created using CV XE GIS and associated GIS Project

Zoom-in View of Schools; School Characteristics
Further zoom-in shows schools labeled with name.  The identify tool is used to show a mini-profile of a school by clicking on the Edna Rowe school marker.
The partial view of the profile shows free and reduced lunch participation and enrollment by grade.

  — view created using CV XE GIS and associated GIS Project

School Attendance Zones
Elementary school attendance (black boundaries) are shown in the next graphic. Dallas ISD has three types of attendance zones (elementary, middle, high school). The query feature is used to show only elementary zones. Click graphic for larger view showing more detail.

  — view created using CV XE GIS and associated GIS Project

Cities/Places & School District
Cities/places are shown in the next graphic (cross-hatch pattern) in context with the school district. Places are non-incorporated areas of population concentration. Click graphic for larger view showing more detail; adjacent city/places shown with yellow diagonal cross-hatch pattern.


  — view created using CV XE GIS and associated GIS Project

Road Infrastructure
Roads/streets are added to the view as shown in the next graphic. Vital to student transportation planning and management, the street density view also helps view the scope of build-out. Click graphic for larger view showing more detail; mini-profile shows attributes of street segment by school/pointer.

  — view created using CV XE GIS and associated GIS Project

Schools in Context of Urban/Rural Geography
Census blocks are categorized as urban or rural based on Census 2010. The graphic below shows urban census blocks with an orange fill pattern. It is easy see that most of Dallas ISD is urban; but a large area in the southeast part of the district is rural. See related K-12 Schools by Urban/Rural Status
.

  — view created using CV XE GIS and associated GIS Project

Percent Population in Poverty by Census Tract
Census tracts are statistically defined geographic areas covering the U.S. wall-to-wall (73,057 areas). The view below shows patterns of percent population in poverty by census tract. Click on graphic to view larger view. Choose from hundreds of demographic-economic measures to assess patterns of well-being, age distribution, housing structure and age, educational attainment, housing value, race/origin, employment, language spoken at home among many others.

  — view created using CV XE GIS and associated GIS Project

See zoom-in view of Edna Rowe school vicinity with tract and %poverty labels

Patterns of Economic Prosperity by Block Group
Block groups are statistically defined geographic areas covering the U.S. wall-to-wall (217,740 areas) and nest within census tracts (see above). Block groups (BGs) provide a finer geographic granularity compared to census tracts. The view below shows patterns of economic prosperity as measured by the median household income (MHI). MHI interval/color patterns are shown in the highlighted layer at left of the map. Click on graphic to view larger version that uses the MHI as a label for each BG. Choose from hundreds of demographic-economic measures to assess patterns of well-being. This view illustrates use of transparency setting to “see through” the pattern layer to view the topology/road infrastructure.


  — view created using CV XE GIS and associated GIS Project

Dallas County Block Group Demographic-Economic Characteristics
Use the interactive table to view, rank compare Dallas County block group demographic-economic characteristics. See about Dallas County demographic trends. All block groups for the county are included in the table. Optionally key in an address using the location-based demographics tool to determine the block group code of interest. You can then use the Find button below the table to locate that block group. See about using block group codes — a 12 character code uniquely identifying that area.

Block Groups in Vicinity of School — Interactive Table
The graphic below illustrates use is the Dallas County block group interactive table. Block groups in census tract “48113012206” are shown in the table. This tract was selected as it contains the Edna Rowe school (location used above in maps). The school’s address was used in the location-based lookup tool. Do this for any school or address in Dallas County. It is easy to see that the Gini Index is low indicating high degree of income equality. It is easy to see and compare the number and type of housing units, median income, housing values, and rent. Try this process yourself:
1 – enter an address using this tool to obtain a census tract code see this example.
2 – below the interactive table click ShowAll button, enter your 11 character tract code, click Find.
All block groups in this tract will show as rows in the table.

Data Analytics Lab Session
Join me in a Data Analytics Lab session. There is no fee. Discuss how tools and methods reviewed in this section can be applied to your situation.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

Demographic-Economic Patterns: Composite & Related Geography

.. we often need data for study areas that do not conform to conventional political/statistical geography. The geography for a market, sales territory, impact zone or other type of study area often do not align with political or statistical geographic areas for which relevant demographic-economic data are available. While the interest might be in demographic-economic characteristics for a particular county, patterns and trends within a county cab vary widely for sub-county geography such as ZIP code areas, census tracts, cities, school districts and other types of geography. It is important to be able to examine the composite, or drill-down, geography for a larger area. Related geography are equally important. Even though primary interest might be in three ZIP code areas, knowing about patterns in related, contiguous ZIP codes is also important. This section illustrates how to examine semi-comprehensive demographic-economic characteristics and trends using organized profiles for alternative geography.

Patterns of Economic Prosperity by Neighborhood
ZIP Code Area 60565
in Naperville, IL area — bold black boundary

– note this ZIP code area intersects with many census tracts;
    … in many cases tract boundaries are not coterminous with ZIP code.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

More information — get for your areas anywhere in U.S.

Illustrative set of different types of geography; Naperville, IL; Chicago metro.
Click links to view full profile.
ZIP Code Area 60565 — Naperville, IL area — see graphic above
Census Tract 17197880119 — Naperville, IL area — see graphic below
Naperville city, IL — see graphic below
Naperville School District, IL — see graphic below
DuPage County, IL — see graphic below

Patterns of Economic Prosperity by Neighborhood
Census tract 17197880119
in Naperville, IL area — bold black boundary

– ZIP code 60565 shown with red boundary.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

Patterns of Economic Prosperity by Neighborhood
Naperville, IL city
— cross-hatched pattern, bold black boundary

– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

Patterns of Economic Prosperity by Neighborhood
Naperville School District, IL
— cross-hatched pattern, bold black boundary

– Naperville city shown with semi-transparent cross-hatch pattern.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

Patterns of Economic Prosperity by Neighborhood
DuPage County, IL
— cross-hatched pattern, bold black boundary

– Naperville city shown with semi-transparent cross-hatch pattern.
– colors show patterns of median household income by census tract
– view developed with CV XE GIS … view full profile

There are many other ways to use composite and related geography in data analytics. GIS tools enable wide-ranging geospatial analysis not covered in detail here. See more about this topic in the data analytics program.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.

Local Area Labor Force Characteristics

.. on the one hand, there are many choices for accessing and using local area labor force characteristics data; on the other, the available options often fall short of meeting the needs.  This section provides a guide to accessing, integrating and using selected local area labor force characteristics data for wide-ranging analysis and decision-making applications. A “local area” as used here refers mainly to city/place, county and sub-county geography (census tract and ZIP Code area). See related Web section.

ACS 2013 Employment Situation by ZIP Code Area
  — Using GIS Tools for Visual & Geospatial Analysis

The American Community Survey (ACS) 5-year estimates have evolved into a primary resource for examining labor force characteristics. One important limitation is the time lag between data availability and reference date. The ACS 2013 data (released December 2014) are for the 5-year period 2009-2013 and centric to mid-2011; in mid-2015 these estimates are 4 years old.

However, these data can provide powerful insights. The following graphic shows the percent unemployed by ZIP Code area in the Houston, Texas/Harris County (bold black boundary) area. The ACS 2013 5-year estimates of the unemployment rate, included in the interactive table below, are shown as a thematic map. It is easy to see which areas/ZIP codes are experiencing higher/lower unemployment rates.

Click for larger view; larger view shows mini-profile of ZIP Code 77077.
See more ZIP Code demographic-economic data resources.
View created using CV XE GIS.

This section updates in mid-March (watch in calendar) with new data access information relating to data resources summarized below. The present version of this section is focused on:
1) upcoming updates to the Bureau of Labor Statistics Local Area Unemployment
Statistics program and how this affects labor force data availability and use and
2) an interactive table providing access to ZIP Code area labor force
characteristics based on the American Community Survey 2013 5-year data.

Overview
Statistical programs that provide local area labor force data include:
American Community Survey
  — annual updates, place of residence based
  — geography: block group, ZIP Code area, city/place, census tract up
  — only the ACS provides labor force data for every congressional district
• ProximityOne current estimates and projections
  — annual updates, place of work & residence based
  — geography: ZIP Code area, city/place, census tract up
• BLS Local Area Unemployment Program (city/place, county up) — see below
• BLS Quarterly Census of Employment and Wages
  — quarterly, long time series, place of work based;
  — geography: county up
• BEA Regional Economic Information System
  — annual, long time series
  — geography: county up
• Decennial census Census 2000 and earlier

Advantages/disadvantages, strengths/weaknesses and more about accessing, integrating and using these data will be included in the mid-March update.

BLS LAUS Program. Effective with the March 2015 release of the Bureau of Labor Statistics Local Area Unemployment Statistics (LAUS) estimates for metropolitan areas and smaller geography, new data and methodology are available for analyzing local area employment patterns. These new data have several far-reaching implications for local area labor force analysis.

The fact that the new data are for the 2013 current vintage metropolitan areas CBSAs is very important. It makes the LAUS data consistent with CBSA geography used in other Federal statistical programs including the the American Community Survey (ACS).

The new LAUS estimation methodology makes the local area employment and unemployment estimates more consistent with ACS data which are used in the LAUS estimation. Use of the annually updated ACS data in the LAUS estimates development is an important update to Census 2000-related data previously used in the estimation process. Other methodological changes should lead to more accurate and useful local area employment estimates for sub-county areas not otherwise available.

ACS 2013 Labor Force Characteristics by ZIP Code Area
  — Interactive Table

Use the interactive table in the related Web section to view, rank, compare, query selected labor force characteristics by ZIP code area. These data are based on the ACS 2013 5 year estimates (same data as used in map view above).

Houston area ZIP Code 77007 (shown at pointer in this view) has an ACS 2013 5-year estimated unemployment rate of 3.8%. See ZIP code 77007 in context of all Texas ZIP code areas in the following graphic (click for larger view). Among all 1,934 Texas ZIP code areas, ZIP code 77007 is ranked 201 (there are 200 ZIP code areas with a lower unemployment rate).

Use the interactive table to perform similar analyses on ZIP code areas of interest.

See the main Local Area Labor Force Web section for mid-March updates (watch in calendar).

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data.