Category Archives: Disability

Making & Using Custom 115th Congressional District Maps

.. using GIS resources to create custom 115th Congressional District maps .. use the methods, data and tools described in this section to develop custom congressional district maps. View patterns of economic prosperity by neighborhood for one or all congressional districts. Flexibly associate a congressional district boundary with related geography and subject matter.  See related Web section for more details.

Join the Congressional District-State Legislative District (CDSLD) Group .. be a part of the community. .. click here to join .. there is no cost.

Coming up … mapping/analyzing school district finances in context of the 115th Congressional Districts (June 2017).

See the related section on Making/Using 113th Congressional District Maps.
.. view different congressional district vintages in same map.

115th Congressional Districts by Incumbent Party Affiliation
This view and related GIS project/data update when changes are made to the 115th Congressional Districts incumbents (last updated 5/10/17). Party affiliation shown in this view is also available in the related interactive table. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Use the Geographic Information System (GIS) tools and data to view/show congressional district in context with roads, landmarks and other geography. Flexibly add labels. Create pattern views. Add your own data.

Patterns of Economic Prosperity by 115th Congressional District
The following graphic shows patterns of ACS 2015 median household income (MHI) by 115th Congressional District. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– use the GIS project and tools see below to create different views.

Examine Characteristics of any Congressional District
The following graphic shows patterns of ACS 2015 median household income (MHI) by census tract in context of 115th Congressional Districts in a region of North Carolina. CD 3712 (Charlotte area) is shown with bold boundary. It is easy to see which areas/tracts have different levels of economic prosperity.

– View developed using CV XE GIS and related GIS project.
– use the GIS project and tools see below to create different views; add other layers.

Creating congressional district maps is often specific to a particular analysis, zoom-view, labeling, combination of different geographies or other considerations. While there are no estimates of unemployment by congressional district, using GIS tools it is possible to view/geospatially analyze patterns of unemployment within congressional district by county, census tract, block group and other geography.

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.

New ACS 2015 1-Year Demographic-Economic Data

.. essential data to assess where we are, how things have changed and how things might change in the future down to the sub-neighborhood level. The American Community Survey (ACS) is a nationwide survey designed to provide annually updated demographic-economic data for national and sub-national geography. ACS provides a wide range of important data about people and housing for every community across the nation. The results are used by everyone from planners to retailers to homebuilders and issue stakeholders like you. ACS is a primary source of local data for most of the 40 topics it covers, such as income, education, occupation, language and housing. ProximityOne uses ACS to develop current estimates on these topics and 5-year projections. This section is focused on ACS 2015 data access, integration and use and is progressively updated.

New ACS 2015 1-year estimates are available as of September 15, 2016.

Importance of ACS: Assessing Demographic-Economic Change
Oil prices plummeted in late 2014. How has this affected people and households in areas hardest hit? Find out for wide-ranging geographies using the ACS 2015 1-year estimates. Compare to ACS 2014 1-year estimates. Use the ACS 2016 1-year estimates (September 2017) to see how the impact has continued. Demographic-economic conditions change for many reasons; oil price changes are just one.

Keep informed about ACS developments and related tools and applications:
• Updates are sent to ProximityOne User Group members (join here).
… access special extract files and GIS projects available to members.
• ACS updates and applications are covered in the Data Analytics Blog.
• ACS data access, integration & use … join us in a Data Analytics Lab session.

In the weeks ahead, the following ProximityOne information resources will be updated with new ACS 2015 1-year data:
U.S.-State-Metro Interactive Tables
• Demographic component section of Metro Situation & Outlook Reports .. example for Dallas metro
• Housing characteristics component section of Metro Situation & Outlook Reports .. example for Dallas metro
Demographic-Economic Trend Profiles
• Special study reports.

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.

Small Area Disability Demographics

Goto ProximityOne   People with disabilities bring unique sets of skills to the workplace, enhancing the strength and diversity of the U.S. labor market. They make up a significant market of consumers, representing more than $200 billion in discretionary spending and creating technological innovation and entrepreneurship. People with disabilities also often rely on various government interventions to maintain their participation in the community. Demographic data about people with disabilities help stakeholders better understand needs and make more informed decisions relating to a wide range of topics concerning people with disabilities.

New Disability Demographics
Disability demographics from the American Community Survey (ACS) have been available for cities, counties and larger areas with population over 65,000 for a few years. New as of December 2013, are ACS 2012 5-year (ACS0812) disability demographics available for all cities, school districts, counties and geographies down to the census tract level — and ZIP code area. Disability demographics are often “masked” when analyzed for larger population areas. Masked, not in the sense of suppressed data, but that concentrations that might be identified at the census tract level may become less prominent when viewed in the aggregate of county or higher level geographies. This section reviews disability-related ACS0812 data available for these small area geographies and how they can be used to facilitate decision-making.

Disability Concepts
Subject matter categories about people with disabilities from ACS generally involve limitations with vision, hearing, cognitive, ambulatory, self-care or independent living difficulty.

• Vision — blindness or serious difficulty seeing even when wearing glasses
• Hearing — deafness or serious difficulty hearing
• Cognitive — difficulty concentrating, remembering or making decisions
• Ambulatory — serious difficulty walking or climbing stairs
• Self-care — difficulty bathing or dressing
• Independent living — difficulty going outside to shop or visit a doctor’s office

Visual Analysis of Disability Patterns by Census Tract
The following view shows the population ages 5-17 years with disabilities (ACS0812 estimates) by census tract for Harris County, Texas (Houston area). The inset legend shows color patterns associated with data from Table B18101 (see below).
acs0812_b18101_48201tracts1
The above view was developed using the CV XE GIS software with a GIS project. The GIS project includes a county by census tract layer with Table B18101 (see below) integrated subject matter. This particular view shows patterns of the sum of items B18101007 (males age 5-17 years with disability) and B18101026 (females age 5-17 years with disability). View all items in this table by opening excel file B18101 in the section below. Members of the ProximityOne User Group may download and use this project to develop similar views on their computer. Add other geographies to the view such as school districts or cities. Add your own data from any source. Join the User Group now, no fee.

Disability Subject Matter Data/Tables
View the scope of ACS 2012 5-year estimates subject matter using the interactive table at http://proximityone.com/acs0812.htm. Sort on the rightmost column and scroll to Disabilities. These same tables are listed below. Click a link on the table number to view a sample of the data (an excel file will open). All data tables are provided for Houston ISD (HISD), Texas school district. The same scope of data are available for any school district.

Table B18101 shows that there are more than 9,000 K-12 school age children with disabilities in Houston ISD (3,493 females, 6,133 males). Using the additional Table B18101 iterations, the distribution of this population can be examined by race and origin. Of course, school age children without disabilities can be impacted by other household members that do have disabilities. Demographics provided in these tables show characteristics for the total population and many age groups. Tables B18102 through B18107 provide insights into the number of persons by age and gender by type of disability. Table B18135 provides data on health insurance coverage. Employment status and workforce data are provided by Tables C18120 and C18121. Earnings and poverty characteristics data are provided by Tables B18140, C18130 and C18131.

ACS 2012 Disability Tables
B18101 — Sex by Age by Disability Status
B18101A — Age by Disability Status:  White alone
B18101B — Age by Disability Status:  Black or African American alone
B18101C — Age by Disability Status: American Indian and Alaska Native alone
B18101D — Age by Disability Status: Asian alone
B18101E — Age by Disability Status: Native Hawaiian and other Pacific Islander
B18101F — Age by Disability Status: Some other race alone
B18101G — Age by Disability Status: Two or more races
B18101H — Age by Disability Status: White alone, not Hispanic or Latino
B18101I — Age by Disability Status: Hispanic or Latino
B18102 — Sex by Age by  Hearing Difficulty
B18103 — Sex by Age by Vision Difficulty
B18104 — Sex by Age by Cognitive Difficulty
B18105 — Sex by Age by Ambulatory Difficulty
B18106 — Sex by Age by Self-Care Difficulty
B18107 — Sex by Age by Independent Living Difficulty
B18135 — Age by Disability Status by Health Insurance Coverage
B18140 — Median Earnings in the Past 12 Months
C18108 — Age by Number of Disabilities
C18120 — Employment by Disability Status
C18121 — Work Experience by Disability Status
C18130 — Age by Disability Status by Poverty Status
C18131 — Ratio of Income to Poverty Level Past 12 Months by Disability

Accessing & Using the Data
Access the above tables using the CV APIGateway. Integrate the disability-related data with other demographic-economic data from ACS 2012 and other data sources. Save data for multi-geography such as all census tracts for a county. Merge these data into a county by tract shapefile and use the CV XE GIS software to visually examine small area patterns of the population with disabilities.