Naturally Occurring Retirement Communities in Path of Hurricane Ian

.. 25.8 million U.S. households had a head of household age 65 years or over in 2010; 22.1% of total households. 3.1 million households with head of household 65 years or over were located in 10,201 “naturally occurring retirement communities” (NORCs) — areas where the percent of head of household age 65 or over is 40 percent or more. Has the number of NORCs tripled by now? Where and how much .. a next blog.

Here, we review Naturally Occurring Retirement Communities in the Path of Hurricane Ian by block group (BGs) in Lee County, FL … using VDA Web GIS. The same process can be applied to any area.

The following view shows a map view of the BGs meeting the criteria. A partial list of the BGs are shown in the table below the map. In the graphic, BGs meeting the criteria show with blue cross-hatch. Zoom in, label, get a profile if viewing real-time. In the graphic, for example, BG 120710019151 (state 12, county 171, tract 001951, BG code 1) has a total Census 2020 population of 2,061.

Step-by-Step Guide
See this VDA Web GIS tutorial showing how to develop a similar view for areas of interest.

About VDA Web GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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. Join Warren on LinkedIn.

Examining Majority-Minority Population by Census Tract

.. a geographic area, such as a census tract or county, has a majority-minority (MM) population when the percent of the population less White, NonHispanic population is more than 50-percent or more of the total population. This section examines patterns of MM by 2020 census tract in the Houston, TX area using the VDA Web GIS (VDA). You can use VDA to examine patterns of MM by tract for areas of interest. All you need is a Web browser and Internet.

MM Tracts in the Houston Area
The following graphic shows patterns of the MM by tract in the Houston metro developed with VDA. The map shows tracts having more than 50% MM population with a red/salmon color. Tracts having 50% or less MM population are shown in blue/green/yellow. Harris County, TX has 1,115 2020 census tracts; 854 of these tracts have a MM population. See the partial list of those tracts by tract code and %MM in the table below the map. A query was used to determine the number of tracts meeting a criteria and sorted in descending order by %MM.

See this VDA Guide section for a step-by-step description
of how you can develop this or a similar view/analysis.

Percent Majority-Minority is a demographic attribute/measure for a geographic area. Like population density or percent population of a certain age, %MM can provide insights for stakeholders or analysts.

About VDA Web GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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. Join Warren on LinkedIn.