The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health.
|Dataset Page||Main webpage for the dataset.|
|How To Manual||An illustrated guide to using, presenting and analysing the indicators.|
|Technical Manual||Primary technical manual, with detailed descriptions of how each indicator was constructed.|
How the data were processed
This data package combines original files that were broken into seperate Excel files, and splits files on the type of geographic grain, so each of the output files consists of only one geography, covering the whole state. For instance, the original release has four Public_Transit_Access files, one each for large regions of California. These files were combined, then split again into 5 files, one each for the county, tract, place, region and CMSA geographic aggregations.
geotype field has a code the describes the type of geography used in
aggregating each row. These geographies are generally Census geographies,
and are specified with Census geoids, in the
geotypevalue field. The
geotype codes are:
STThe whole state of California
CDA county subdivision
PLA Census Designated Place
REA Sub-state region
ZCZCTA, the Census version of a ZIP code area.
R4Consolidated Metropolitan Statistical Areas
MSMetropolitan Statistical Area
These values, excluding RE, R4 and MS are converted to a GVid for linking to other files.
On most files the state code is
CA, but in the Open Space file it is
These geotype codes are all mapped to names and used as part of the file names.
Other important processing steps included:
ind_id, which have a name and number for each of the indicators, were removed from the data and used as table descriptions. These value appear to be constant in all rows in a file.
- Some very large RSE values have been changed to NULL
As of Dec 1, 2015, In the
Neighborhood Change files, the Relative Standard Error (rse) column is often computed for values that are very close to zero, so the RSE is very large. In other files in this dataset, the rse value is capped
at 100. As per Dulce Bustamante-Zamora at CDPH, these values should be blank, (NULL) so this correction is made for rows where the difference is 0.
reportyear field can be either a single integer year, or it may be a range of years, which is represented as a string.
|housing_cost||HCI Indicator 106.0: Percent of households spending more than 30% (50%) of monthly household income on monthly gross rent or selected housing costs||t04p0A003|
|neighborhood_change||HCI Indicator 772.0: Neighborhood change: 10-year change in number of households by income and race/ethnicity||t04p0B003|
|household_type_tracts||HCI Indicator 746.0: Household by type of family and head of household||t04p0C003|
|household_type||HCI Indicator 746.0: Household by type of family and head of household||t04p0D003|
|living_wage||HCI Indicator 770.0: Living wage and percent of families with incomes below the living wage||t04p0E003|
|walk_bicycyle||HCI Indicator 778.0: Percent of population aged 16 years or older whose commute to work is 10 minutes /day or more by walking or biking||t04p0F003|
|food_affordability||HCI Indicator 757.0: Food affordability for female-headed household with children under 18 years||t04p0G003|
|healthy_food||HCI Indicator 75.0: Modified retail food environment index||t04p0H003|
|poverty_rate||HCI Indicator 754.0: Overall, concentrated, and child (0 to 18 years of age) poverty rate||t04p0I003|
|traffic_fatalities||HCI Indicator 753.0: Annual number of fatal and severe road traffic injuries per population and per miles traveled by transport mode||t04p0J003|
|violent_crime||HCI Indicator 752.0: Number of Violent Crimes per 1000 Population||t04p0K003|
|transport_work||HCI Indicator 42.0: Percent of residents mode of transportation to work||t04p0L003|
|household_crowding||HCI Indicator 137.0: Percent of household overcrowding (> 1.0 PPR) and severe overcrowding (> 1.5 PPR)||t04p0M003|
|high_school_ed||HCI Indicator 369.0: High School or Greater Educational Attainment in the Population Aged 25 Years and Older||t04p0N003|
|alcohol_outlets||HCI Indicator 774.0: Percent of Population within 1/4 Mile of Alcohol Outlets by Type of Establishment Sales||t04p0O003|
|unsafe_water||HCI Indicator 426.0: Drinking water quality (Percent of the population served by community water systems not meeting regulations of the Safe Drinking Water Act)||t04p0P003|
|air_quality||HCI Indicator 776.0: Average Ambient PM2.5 concentration (microgram/m3)||t04p0Q003|
|jobs_housing_ratio||HCI Indicator 768.0: Jobs to housing ratio||t04p0R003|
|unemployment||HCI Indicator 290.0: Unemployment rate||t04p0s003|
|income_inequality||HCI Indicator 556.0: Income inequality: Gini coefficient describing the amount of total annual community income generated by the number of households||t04p0S003|
|registered_voters||HCI Indicator 653.0: Percent of adults age 18 years and older who are registered voters||t04p0t003|
|abuse_neglect||HCI Indicator 741.0: Percent of children (under 18) reported with neglect or physical or sexual abuse||t04p0u003|
|jobs_employed_ratio||HCI Indicator 769.0: Jobs to employed residents ratio||t04p0v003|
|miles_traveled||HCI Indicator 39.0: Miles traveled per capita by mode (car, public transit, walk/bike)||t04p0w003|
|ozone||HCI Indicator 761.0: Average annual number of unhealthy days of ozone||t04p0x003|
|public_transit||HCI Indicator 51.0: Percent of population within 1/2 mile of major transit stop||t04p0y003|
|open_space||HCI Indicator 469.0: Percent of Population within ½ Mile of Park, Beach, Open Space, or Coastline||t04p0z003|
Too many sources to display. Download the sources.csv file for a complete list.