The County Health Rankings show us that where we live matters to our health. The health of a community depends on many different factors - ranging from health behaviors, education and jobs, to quality of health care, to the environment.

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Data Sources and Measures

The County Health Rankings team synthesizes health information from a variety of national data sources to create the Rankings. Most of the data we use are public data available at no charge. Measures based on vital statistics data, sexually transmitted disease rates, and Behavioral Risk Factor Surveillance System (BRFSS) survey data were calculated for us by staff at the National Center for Health Statistics and other units of the Centers for Disease Control and Prevention (CDC). The same is true for our health care quality measures, which were calculated for us by the authors of the Dartmouth Atlas of Healthcare, using Medicare claims data. Another key data source, primarily for social and economic variables, is the American Community Survey. We download these data sets and, where needed, calculate the estimates ourselves. Similarly, we downloaded publicly available data on violent crime and some built environment measures, and calculated point estimates.
 
We have compiled the following summary information regarding the 2012 measures:
A brief description of each of our data sources follows.
 

The Behavioral Risk Factor Surveillance System (BRFSS) is a national random digit dial (RDD) telephone survey. Data obtained from the BRFSS are representative of the total non-institutionalized population over 18 years of age living in households with a land line telephone. For the County Health Rankings, data from the BRFSS are used to measure various health behaviors and health-related quality of life (HRQOL) indicators. All data from the BRFSS were weighted by population and the HRQOL measures were age-adjusted. Statewide results are available online at www.cdc.gov/brfss/. We obtained county-level measures, in almost all instances aggregated over several years, from the National Center for Health Statistics (NCHS)/Centers for Disease Control and Prevention (CDC): NCHS/CDC calculated these county-level measures and provided them to the County Health Rankings.

 

Data on deaths and births were provided by NCHS and were drawn from the National Vital Statistics System (NVSS). These data are submitted to the NVSS by the vital registration systems operated in the various jurisdictions legally responsible for the registration of vital events – births, deaths, marriages, divorces, and fetal deaths.

The National Diabetes Surveillance System provides county-level estimates of obesity, physical inactivity, and diabetes (available online at: http://www.cdc.gov/diabetes/statistics/index.htm) using data from CDC's Behavioral Risk Factor Surveillance System (BRFSS) and data from the U.S. Census Bureau’s Population Estimates Program. The county-level estimates are based on indirect model-dependent estimates (Rao et al, 2003; Malec et al, 1997). The model-dependent approach employs a statistical model that “borrows strength” in making an estimate for one county from BRFSS data collected in other counties. Bayesian multilevel modeling techniques were used to obtain estimates. The model specification is essentially the same as Malec et al, 1997.

Data on sexually transmitted infections were provided by the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP).  NCHHSTP is responsible for public health surveillance, prevention research, and programs to prevent and control human immunodeficiency virus (HIV) infection and acquired immunodeficiency syndrome (AIDS), other sexually transmitted diseases (STDs), viral hepatitis, and tuberculosis (TB). Center staff work in collaboration with governmental and nongovernmental partners at community, state, national, and international levels, applying well-integrated multidisciplinary programs of research, surveillance, technical assistance, and evaluation.

The air quality measures were estimated using an innovative strategy designed by the Public Health Air Surveillance Evaluation (PHASE) project team, which includes researchers from the Centers for Disease Control and Prevention (CDC) and the U.S. Environmental Protection Agency (EPA). Previously, valid and reliable air quality estimates were difficult to obtain for areas without an adequate number of air quality monitors. The EPA’s first step to address this problem was the creation of the Community Multi-Scale Air Quality Model (CMAQ), an air quality simulation model that uses weather and emissions data to estimate chemical concentrations in the air. To improve upon CMAQ, the PHASE project uses both CMAQ output and monitor data in a hierarchical spatial-temporal model to estimate daily ozone and fine particulate matter concentrations throughout the year.  As a result, researchers can accurately model peak fine particulate matter and ozone concentrations for each day in the year and, using National Ambient Air Quality Standards, estimate the number of days that the air quality was poor for sensitive populations due to these contaminants. The County Health Rankings uses these air quality estimates for all counties in the continental United States. For more information on the EPA’s Community Multi-Scale Air Quality Model, visit http://www.epa.gov/asmdnerl/CMAQ/.

The Area Resource File is a collection of data from more than 50 sources, including: American Medical Association, American Hospital Association, US Census Bureau, Centers for Medicare & Medicaid Service, Bureau of Labor Statistics, and the National Center for Health Statistics. The Area Resource File is available for purchase at http://arf.hrsa.gov/purchase.htm.

The American Community Survey (ACS) is a nationwide survey designed to provide communities a fresh look at how they are changing. It is a critical element in the Census Bureau's reengineered decennial census program. The ACS collects and produces population and housing information every year instead of every ten years. For the County Health Rankings, American Community Survey data are used to obtain measures of social and economic factors. Census and ACS data are available at http://factfinder2.census.gov.

The U.S. Census Bureau's Small Area Health Insurance Estimates (SAHIE) program produces estimates of health insurance coverage for states and all counties. In July 2005, SAHIE released the first nation-wide set of county-level estimates on the number of people without health insurance coverage for all ages and those under 18 years old. SAHIE releases estimates of health insurance coverage by age, sex, race, Hispanic origin, and income categories at the state-level and by age, sex, and income categories at the county-level. These data are available at http://www.census.gov/did/www/sahie/.

The U.S. Census Bureau, with support from other federal agencies, created the Small Area Income and Poverty Estimates (SAIPE) program to provide more current estimates of selected income and poverty statistics than those from the most recent decennial census.  Estimates are created for school districts, counties, and states. The main objective of this program is to provide updated estimates of income and poverty statistics for the administration of federal programs and the allocation of federal funds to local jurisdictions. These estimates combine data from administrative records, intercensal population estimates, and the decennial census with direct estimates from the American Community Survey to provide consistent and reliable single-year estimates. These model-based single-year estimates are more reflective of current conditions than multi-year survey estimates.  At the county level, SAIPE provides estimates on children ages 5–17 in families in poverty, children under age 18 in poverty, all people in poverty, and median household income. These data are available at http://www.census.gov/hhes/www/saipe/.

County Business Patterns provides data on the total number of establishments, mid-March employment, first quarter and annual payroll, and number of establishments by nine employment-size classes by detailed industry for all counties in the United States and the District of Columbia.   ZIP Code Business Patterns presents data on the total number of establishments, employment and payroll for more than 40,000 5-digit ZIP Code areas nationwide. In addition, the number of establishments for nine employment-size categories is provided by detailed industry for each ZIP Code.  Most ZIP Codes are derived from the physical location address reported in Census Bureau programs. The Internal Revenue Service provides supplemental address information.  These data are available at http://www.census.gov/econ/cbp/index.html.

The Uniform Crime Reporting (UCR) Program was conceived in 1929 by the International Association of Chiefs of Police to meet a need for reliable, uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics. Today, several annual statistical publications, such as the comprehensive Crime in the United States, are produced from data provided by nearly 17,000 law enforcement agencies across the United States. 

Since 1996, the Dartmouth Atlas of Health Care has examined patterns of health care delivery and practice across the United States, and evaluated the quality of health care Americans receive. The research has revealed striking variations in the amount of health care you are likely to receive depending on where you live. This is true not only across states and regions, but within individual states and cities. The very large claims databases used in the Dartmouth Atlas Project come from the Centers for Medicare and Medicaid Services (CMS), the federal agency that collects data for every person and provider using Medicare health insurance. Access to this data is made available for research purposes. Normally, the Dartmouth Atlas reports data by hospital service area and hospital referral region but, for the County Health Rankings, staff from the Dartmouth Institute identified and calculated a small subset of quality of care measures by county.

Average freshman graduation rates by county were estimated based on school district information provided to us by the National Center for Education Statistics (NCES). NCES is the primary federal entity for collecting and analyzing data related to education.

Limited access to healthy foods was calculated using data from the USDA Food Environment Atlas.  This resources assembles statistics on food environment indicators to stimulate research on the determinants of food choices and diet quality.

 

 

Rao JNK. Small Area Estimation. Ch.10:223:280. John Wiley & Sons; Hoboken, New Jersey, 2003. 

Malec D, Sedransk J, Moriarity CL, LeClere FB. Small Area Inference for Binary Variables in the National Health Interview Survey. Journal of the American Statistical Association 1997;92(439):815–826.