chronicdata-cdc-gov/places-local-data-for-better-health-census-tract-4ai3-zynv
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Updated 10 months ago
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PLACES: Local Data for Better Health, Census Tract Data 2020 release

This dataset contains model-based census tract-level estimates for the PLACES project 2020 release. The PLACES project is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code tabulation Areas (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 27 measures: 5 chronic disease-related unhealthy behaviors, 13 health outcomes, and 9 on use of preventive services. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2018 or 2017 data, Census Bureau 2010 population data, and American Community Survey (ACS) 2014-2018 or 2013-2017 estimates. The 2020 release uses 2018 BRFSS data for 23 measures and 2017 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening). Four measures are based on the 2017 BRFSS because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

Columns

NameSocrata field nameColumn name in sgr mountData typeDescription
Data_Value_Unitdata_value_unitdata_value_unitTextThe data value unit, such as "%" for percentage
DataValueTypeIDdatavaluetypeiddatavaluetypeidTextIdentifier for the data value type
CountyNamecountynamecountynameTextCounty name
YearyearyearTextYear
StateAbbrstateabbrstateabbrTextState abbreviation
Data_Value_Footnote_Symboldata_value_footnote_symboldata_value_footnote_symbolTextFootnote symbol
MeasuremeasuremeasureTextMeasure full name
StateDescstatedescstatedescTextState Name
CategorycategorycategoryTextTopic
TotalPopulationtotalpopulationtotalpopulationNumberTotal population of Census 2010
LocationIDlocationidlocationidTextCensus tract FIPS
CategoryIDcategoryidcategoryidTextIdentifier for Topic/Category
MeasureIdmeasureidmeasureidTextMeasure identifier
Short_Question_Textshort_question_textshort_question_textTextMeasure short name
GeolocationgeolocationgeolocationPointLatitude, Longitude of city centroid (Format: Point(Longitude Latitude))
Data_Value_Footnotedata_value_footnotedata_value_footnoteTextFootnote text
High_Confidence_Limithigh_confidence_limithigh_confidence_limitNumberHigh confidence limit
Low_Confidence_Limitlow_confidence_limitlow_confidence_limitNumberLow confidence limit
Data_Valuedata_valuedata_valueNumberData Value, such as 14.7
Data_Value_Typedata_value_typedata_value_typeTextThe data type, such as age-adjusted prevalence or crude prevalence
LocationNamelocationnamelocationnameTextTract FIPS code
CountyFIPScountyfipscountyfipsTextCounty FIPS code
DataSourcedatasourcedatasourceTextData source
 
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Upstream Metadata