Us Demographic Data By Zip Code
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The Census Bureau first examined all of the addresses within each census block to define the list of ZIP Codes by block. Next, the most frequently occurring ZIP Code within each block was assigned to the entire census block as a preliminary ZCTA code. After all of the census blocks with addresses were assigned a preliminary ZCTA code, blocks were aggregated by code to create larger areas.
Your responses can help determine how much funding your local community will receive for public services. Census population data is used to divide the seats in the U.S. House of Representatives among the 50 states. It can also be used to draw boundaries for state legislative and school districts.
Besides using census data for the benefit of public services, you can also use it for genealogical research. To protect the privacy of people who respond to the U.S. Census, all records are kept confidential for 72 years. Find out what genealogical information is available and where you can access it.
One of the many challenges that social science researchers and practitioners face is the difficulty of relating United States Postal Service (USPS) ZIP codes to Census Bureau geographies. There are valuable data available only at the ZIP code level that, when combined with demographic data tabulated at various Census geography levels, could open up new avenues of exploration.
While some acceptable methods of combining ZIP codes and Census geography exist, they have limitations. To provide additional avenues for merging these data, PD&R has released the HUD-USPS Crosswalk Files. These unique files are derived from data in the quarterly USPS Vacancy Data. They originate directly from the USPS; are updated quarterly, making them highly responsive to changes in ZIP code configurations; and reflect the locations of both business and residential addresses. The latter feature is of particular interest to housing researchers because many of the phenomena that they study are based on housing unit or address. By using an allocation method based on residential addresses rather than by area or by population, analysts can take into account not only the spatial distribution of population, but also the spatial distribution of residences. This enables a slightly more nuanced approach to allocating data between disparate geographies. Please note that the USPS Vacancy Data is constructed from ZIP+4 data that contains records of addresses, it does not contain ZIP+4 data that are associated with ZIP codes that exclusively serve Postal Office Boxes (PO Boxes). As a result, ZIP codes that only serve PO Boxes will not appear in the files.
Though often used for mapping, spatial analysis, and data aggregation careful attention is required when interpreting ZIP Code data relative to other administrative geographies. The following article demonstrates how to more effectively use the U.S. Department of Housing and Urban Development (HUD) United States Postal Service ZIP Code Crosswalk Files when working with disparate geographies.
There are six types of crosswalk files available for download. The first 3 crosswalk files are used to allocate ZIP codes to Census tracts, counties or Core Based Statistical Areas (CBSA). The last three are used to allocate Census tracts, counties or Core Based Statistical Areas to ZIP codes. It is important to note that the relationship between the two types of crosswalk files is not a perfectly inverse one. That is to say, you cannot use the ZIP to Tract crosswalk to allocate Census tract data to the ZIP code level. For that you would have to use the Tract to ZIP crosswalk file.
When a ZIP is split by any of the other geographies, that ZIP code is duplicated in the crosswalk file. In the example below, ZIP code 03870 is split by two different Census tracts, 33015066000 and 33015071000, which appear in the tract column. The ratio of residential addresses in the first ZIP-Tract record to the total number of residential addresses in the ZIP code is .0042 (.42%). The remaining residential addresses in that ZIP (99.58%) fall into the second ZIP-Tract record. So, for example, if one wanted to allocate data from ZIP code 03870 to each Census tract located in that ZIP code, one would multiply the number of observations in the ZIP code by the residential ratio for each tract associated with that ZIP code. Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.
When a Census tract, county or CBSA is split by a ZIP code, that tract, county or CBSA code is duplicated in the crosswalk file. In the example below tract 01001020200 is split by two different ZIP codes, 36008 and 36067, which appear in the ZIP column. The ratio of residential addresses in the first tract-ZIP record to the total number of residential addresses in the tract is .0272 (2.72%). The remaining residential addresses in that tract (97.28%) fall into the second tract-ZIP record. So, for example, if one wanted to allocate data from Census tract 01001020200 to the ZIP code level, one would multiply the number of observations in the Census tract by the residential ratio for each ZIP code associated with that Census tract. Note that the sum of each ratio column for each distinct ZIP code may not always equal 1.00 (or 100%) due to rounding issues.
HUD is unable to geocode a small number of records that we receive from the USPS. As a result, there may be some 5-digit USPS ZIP codes that will not be included in these crosswalk files. Less than 1% of the total number of active 5-digit ZIP codes in the country are excluded from the current version of the crosswalk files. Since the HUD geocoding base map is updated regularly, an effort is made to re-geocode these records with every new quarter of data. As a result, these crosswalk files will be generated on a quarterly basis and may differ slightly from quarter to quarter.
No. Unfortunately, the underlying data used to create the Crosswalk Files does not contain USPS Recommended City Names. However, Recommended City Names can be searched on the USPS ZIP Code Lookup page. Please note that Recommended City Names do not match Census defined names, please see Misalignment Between ZIP Codes and Municipal Boundaries: A Problem for Public Health for an analysis.
Demographic information can help your nonprofit to better identify your community's needs and to find gaps in its services. Using this data in a grant proposal can help make a case for the urgency of the community need that your nonprofit's mission addresses.
Find the center's datasets by research area and information about how to use them. The center also publishes wide-ranging analyses. Click on the tabs at the top of the page to find the research that fits your needs.
The National Center for Education Statistics (NCES) (see Organizational Chart) is the primary federal entity for collecting and analyzing data related to education in the U.S. and other nations. NCES is located within the U.S. Department of Education and
According to the group: "SWB provides pro bono statistical and data science services. We work to improve human welfare by providing empirical knowledge using proper applications of statistical principles and best practices so that our clients can make more informed decisions. We focus on areas where access to such resources is limited."
According to the site, "Some programs at the Bureau of Labor Statistics (BLS) make significant amounts of data available for specific demographic categories. The Bureau's demographic categories include sex, age, race, and ethnic origin."
The relationship with health information is fundamental. Identifying information alone, such as personal names, residential addresses, or phone numbers, would not necessarily be designated as PHI. For instance, if such information was reported as part of a publicly accessible data source, such as a phone book, then this information would not be PHI because it is not related to heath data (see above). If such information was listed with health condition, health care provision or payment data, such as an indication that the individual was treated at a certain clinic, then this information would be PHI.
The increasing adoption of health information technologies in the United States accelerates their potential to facilitate beneficial studies that combine large, complex data sets from multiple sources. The process of de-identification, by which identifiers are removed from the health information, mitigates privacy risks to individuals and thereby supports the secondary use of data for comparative effectiveness studies, policy assessment, life sciences research, and other endeavors.
Both methods, even when properly applied, yield de-identified data that retains some risk of identification. Although the risk is very small, it is not zero, and there is a possibility that de-identified data could be linked back to the identity of the patient to which it corresponds.
(B) All geographic subdivisions smaller than a state, including street address, city, county, precinct, ZIP code, and their equivalent geocodes, except for the initial three digits of the ZIP code if, according to the current publicly available data from the Bureau of the Census:(1) The geographic unit formed by combining all ZIP codes with the same three initial digits contains more than 20,000 people; and(2) The initial three digits of a ZIP code for all such geographic units containing 20,000 or fewer people is changed to 000
The implementation specifications further provide direction with respect to re-identification, specifically the assignment of a unique code to the set of de-identified health information to permit re-identification by the covered entity.
If a covered entity or business associate successfully undertook an effort to identify the subject of de-identified information it maintained, the health information now related to a specific individual would again be protected by the Privacy Rule, as it would meet the definition of PHI. Disclosure of a code or other means of record identification designed to enable coded or otherwise de-identified information to be re-identified is also considered a disclosure of PHI. 2b1af7f3a8