Data
The data in the Mapping Broadband Health in America 2023 platform is extracted from leading data sources for broadband and maternal health measures as well as demographic metrics. The three data tables below briefly identify each of the measures (as denominated in the platform), its definition, the primary data source, and the data year. Hyperlinks in the tables direct users to the primary data sources.
- More detailed information about the data that underlies the platform may be downloaded in our Data Explainer (opens PDF file new window) or in the more researcher-focused Data Dictionary (opens new window) accompanying the Mapping Broadband Health in America platform.
- In addition, the mapping platform was built using an Open Integration model that allows users to integrate their own datasets. To view the three-step process, specific code examples, extensibility files and additional instructions, visit GitHub. View the Open Integration process in GitHub. (opens new window)
- Questions on the data in the mapping platform may be sent to us at engagec2h@fcc.gov.
For broadband, we focus on two key dimensions – broadband access and Internet adoption – in addition to critical sub-measures on rurality and speed. Increasingly, adoption and speed are critical to understanding the full picture of broadband connectivity in a community.
| Dimensions | Measures | Primary Data (Data Year) | Description |
|---|---|---|---|
| Access | Broadband Access (Fixed Broadband) | Fixed Broadband Deployment Data from FCC Form 477 (opens new window), FCC Staff Block Estimates (2019) (opens new window) (Note: this data source also applies to all measures in this table except Internet Adoption) | Percentage of the population living in census blocks with access to fixed broadband service at 25/3 Mbps or higher advertised speeds. |
| Rural Access | Percentage of the population living in rural census blocks with access to fixed broadband service at 25/3 Mbps or higher advertised speeds. | ||
| Download Speed (Fixed Download) | Percentage of population living in census blocks with access to fixed broadband service at 25 Mbps or higher advertised download speeds. | ||
| Upload Speed (Fixed Upload) | Percentage of population living in census blocks with access to fixed broadband service at 3 Mbps or higher advertised upload speeds. | ||
| Adoption | Internet Adoption | Internet Access Services Report (opens new window); Form 477 County-Level Connection Data (2019); Form 477 County-Level Tier Data (2019) (opens new window) | The number of residential (consumer) connections per 100 households. |
Data Provider (Release/Access Year): Fixed Broadband Deployment Data from FCC Form 477 (2020) (opens new window); FCC Staff Block Estimates (2020) (opens new window); Internet Access Services Report (2022) (opens new window); Form 477 County Data on Internet Access Services (2023) (opens new window)
For health, and as a part of the 2023 update, the platform now includes recent chronic disease data as well as data on opioids and maternal health. For chronic disease, we focus on four critical dimensions – health outcomes, access to care, quality of care, and health behaviors – where broadband has been shown to enable effective and cost-saving interventions.
| Health Dimensions and Factors | Health Measures | Primary Data (Data Year) | Description |
|---|---|---|---|
| Health Outcomes | Diabetes | United States Diabetes Surveillance System (2017) (opens new window) | Percentage of adults (aged 20 and above) with diagnosed diabetes. |
| Obesity | United States Diabetes Surveillance System (2017) (opens new window) | Percentage of adults (aged 20 and above) that report a body mass index (BMI) greater than or equal to 30 kg/m2. | |
| Poor/Fair Health | Behavioral Risk Factor Surveillance System (2018) (opens new window) | Percentage of adults who consider themselves to be in poor or fair health (age-adjusted). | |
| Sick Days | Behavioral Risk Factor Surveillance System (2018) (opens new window) | Average number of physically unhealthy days reported in the past 30 days (age-adjusted). | |
| Premature Death | National Center for Health Statistics – Mortality Files (2017-2019) (opens new window) | Years of potential life lost before age 75 per 100,000 population (age-adjusted). | |
| Access to Care | Physician Access | Area Health Resource File/American Medical Association (2018) (opens new window) | Ratio of population to primary care physicians. |
| Primary Care Physicians | Area Health Resource File/American Medical Association (2018) (opens new window) | Number of primary care physicians. | |
| Dental Providers | Area Health Resource File/National Provider Identification File (2019) (opens new window) | Number of dentists. | |
| Mental Health Providers | CMS, National Provider Identification (2020) (opens new window) | Number of mental healthcare providers. | |
| Quality of Care | Preventable Hospitalization | Mapping Medicare Disparities Tool (2018) (opens new window) | Rate of hospital stays for ambulatory-care sensitive conditions per 100,000 Medicare enrollees (age-adjusted). |
| Health Behaviors | Smoking | Behavioral Risk Factor Surveillance System (2018) (opens new window) | Percentage of adults who are current smokers. |
| Excessive Drinking | Behavioral Risk Factor Surveillance System (2018) (opens new window) | Percentage of adults reporting binge or heavy drinking during the last 30 days. | |
| Physical Inactivity | United States Diabetes Surveillance System (2017) (opens new window) | Percentage of adults (age 20 and over) reporting no leisure-time physical activity. | |
| Selected Community Factors | Injury Deaths | National Center for Health Statistics – Mortality Files (2015-2019) (opens new window) | Number of deaths due to injury per 100,000 persons. |
| Severe Housing | Comprehensive Housing Affordability Strategy (CHAS) data (2013-2017) (opens new window) | Percentage of households with at least 1 of 4 housing problems: overcrowding, high housing costs, lack of kitchen facilities, or lack of plumbing facilities. |
Data Provider (Release/Access Year): Robert Wood Johnson Foundation & University of Wisconsin Population Health Initiative County Health
Rankings & Roadmaps program (2021) (opens new window)
For opioids, this initial phase of the effort to intersect drug abuse data with broadband focuses on two dimensions of the ongoing crisis – outcomes (mortality rates) and risk factors for overdose (prescription rates); we anticipate that the second phase will include other risk factors and intermediate variables established in the research literature as precursors and drivers of opioid abuse and overdose, as described in the Broadband and Opioids Conceptual Model.
| Dimensions | Measures | Primary Data (Data Year) | Description |
|---|---|---|---|
| Health Outcomes | All Drugs – Death Rate | Multiple Cause of Death 1999-2019 on CDC WONDER Online Database - United States Department of Health and Human Services, Center for Disease Control and Prevention, National Center for Health Statistics (opens new window). (2010-2019) Note: this data source applies to all measures for Health Outcomes | Mortality rate for all drug-related overdose, represented as deaths per 100,000 persons. |
| All Drugs – Death Rate Trends | Percent change in mortality rate (deaths per 100,000 persons) for all drug-related overdose. | ||
| All Opioids – Death Rate | Mortality rate for all opioid-related overdose, represented as deaths per 100,000 persons. | ||
| All Opioids – Death Rate Trends | Percent change in mortality rate (deaths per 100,000 persons) for all opioid-related overdose. | ||
| Prescription Opioids – Death Rate | Mortality rate for all prescription opioid overdose, represented as deaths per 100,000 persons. | ||
| Prescription Opioids – Death Rate Trends | Percent change in mortality rate (deaths per 100,000 persons) for all prescription opioid overdose. | ||
| Synthetic Opioids – Death Rate | Mortality rate for all synthetic opioid overdose, represented as deaths per 100,000 persons. | ||
| Synthetic Opioids – Death Rate Trends | Percent change in mortality rate (deaths per 100,000 persons) for all synthetic opioid overdose. | ||
| Heroin – Death Rate | Mortality rate for all heroin overdose, represented as deaths per 100,000 persons | ||
| Heroin – Death Rate Trends | Percent change in mortality rate (deaths per 100,000 persons) for all heroin overdose. | ||
| Risk Factors | Opioids Prescription Rate | U.S. Opioid Dispensing Rate Maps, Centers for Disease Control and Prevention, National Center for Injury Prevention and Control (sourced from IQVIA Xponent 2006-2020) (opens new window) (2019-2020) Note: this data source applies to all measures for Risk Factors | Rate of retail opioid prescriptions dispensed per 100 persons. |
| Opioids Prescription Trends | Percent change in opioid prescription rate (retail opioid prescriptions dispensed per 100 persons). |
Data Provider (Release/Access Year): CDC
WONDER Online Database (2023) (opens new window); U.S. Opioid Dispensing Rate Maps, CDC, NCIPC (2023) (opens new window)
For maternal health, we incorporate data on maternal mortality and severe maternal morbidity, including up to one year postpartum, as specified in the Data Mapping to Save Moms’ Lives Act, Public Law No. 117-247 (eff. Dec. 20, 2022). We also include select measures related to risk factors for poor maternal health outcomes and access to maternal health care. Given the multifaceted and complex nature of the maternal health crisis, this additional information can help shed light on the drivers or causes of poor maternal health outcomes and provide greater insight for action, including areas where telehealth and other broadband-enabled solutions can be leveraged to improve maternal health.
| Dimensions | Measures | Primary Data (Data Year) | Description |
|---|---|---|---|
| Health Outcomes | Maternal Mortality Rate | National Vital Statistics System, Mortality, (2018-2021) (opens new window) (2018-2021) | Number of maternal deaths up to 42 days postpartum per 100,000 live births. |
| Maternal Deaths | Counties reporting maternal deaths (up to 42 days postpartum) or no maternal deaths. | ||
| Late Maternal Death Rate | Number of maternal deaths up to 1 year postpartum per 100,000 live births. | ||
| Severe Maternal Morbidity Rate | Healthcare Cost and Utilization Project (HCUP) Fast Stats (opens new window) (2019) | Number of women experiencing unexpected outcomes of labor and delivery (20 indicators) per 10,000 in-hospital deliveries. Blood transfusion codes are not included. | |
| Risk Factors | Diabetes - Pre-pregnancy or Gestational | Data downloaded from the Maternal and Infant Health Mapping Tool (2017-2019), a website developed by the Health Resources and Services Administration, Maternal and Child Health Bureau. A local empirical Bayes algorithm was used to provide more stable estimates, particularly for counties with small numbers that would otherwise be unreliable or suppressed to ensure confidentiality. The degree of smoothing is inversely proportional to the number of events. Thus, counties with larger numbers of births will have less smoothing and little to no difference between actual or raw data available on CDC WONDER and smoothed estimates, while counties with smaller numbers of births will borrow strength from neighboring counties to improve the stability of estimates. Estimates are suppressed if there were fewer than 10 events in the county and its adjacent neighbors. For more information: Marshall RJ. Mapping disease and mortality rates using Empirical Bayes estimators. Journal of the Royal Statistical Society. 1991; 40:283-94. | Estimated percentage of live births to women with any diabetes diagnosis (pre-pregnancy or gestational). |
| Hypertension - Pre-pregnancy or Gestational | Estimated percentage of live births to women with any hypertension (pre-pregnancy or gestational). | ||
| Pre-pregnancy Obesity | Estimated percentage of live births to women with pre-pregnancy Body Mass Index (BMI) ≥ 30 kg/m². | ||
| Demographics | Maternal Age | National Vital Statistics System, Natality, 2016-2021 (opens new window) (2019) | Majority of live births to mothers of a specific age group. |
| Poverty | Small Area Income and Poverty Estimates (2019) | Estimated percentage of families or individuals whose total income is below the corresponding official poverty threshold. | |
| Women 15 - 44 Years of Age by Race/Ethnicity | CDC WONDER Single-Race Population Estimates. Produced by the U.S. Census Bureau. Postcensal estimates of the July 1 resident population with six ‘single-race’ race categories as specified in the 1997 Office of Management and Budget (OMB) standards for the collection of data on race and ethnicity: American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Pacific Islander, White, More than one race. (opens new window) (2019) | Number of women of maternal age (15-44 years) by race or ethnicity. | |
| Access to Care | Health Insurance | U.S. Census Bureau Small Area Health Insurance Estimates (SAHIE) (opens new window) (2019) | Percent of persons under 65 with medical insurance. |
| Prenatal Care in the First Trimester | Data downloaded from the Maternal and Infant Health Mapping Tool (2017-2019), a website developed by the Health Resources and Services Administration, Maternal and Child Health Bureau. A local empirical Bayes algorithm was used to provide more stable estimates, particularly for counties with small numbers that would otherwise be unreliable or suppressed to ensure confidentiality. The degree of smoothing is inversely proportional to the number of events. Thus, counties with larger numbers of births will have less smoothing and little to no difference between actual or raw data available on CDC WONDER and smoothed estimates, while counties with smaller numbers of births will borrow strength from neighboring counties to improve the stability of estimates. Estimates are suppressed if there were fewer than 10 events in the county and its adjacent neighbors. For more information: Marshall RJ. Mapping disease and mortality rates using Empirical Bayes estimators. Journal of the Royal Statistical Society. 1991; 40:283-94. | Estimated percentage of live births to women who received first trimester prenatal care. | |
| Maternity Care Deserts | HRSA Area Health Resources Files (opens new window) (2020-2023) | Access to obstetric care in a given county from none (desert) to full. Maternity care deserts are counties without a hospital, birth center, or provider offering obstetric care. | |
| Mental Health Provider Shortages | HRSA Area Health Resources Files (opens new window) (2020-2023) | Population-weighted average score of Mental Health Professional Shortage Areas in a county. Higher scores indicate greater need or shortage. |
Data Provider (Release/Access Year): CDC
WONDER Online Database (2021) (opens new window); Agency for Healthcare Research and Quality, Healthcare Cost and Utilization Project (2022)
(opens new window); March of Dimes (2022) (opens new window); Health Resources and Services Administration (2023)
(opens new window)
For demographics, we rely on several sources including the U.S. Census Bureau data for population metrics and selected social and economic factors, as detailed below.
| Dimensions | Measures | Primary Data (Data Year) | Description |
|---|---|---|---|
| Population | Population | U.S. Census Bureau County Population Totals: 2010-2019 (opens new window); FCC Staff Block Estimates (2019) (opens new window) (Note: this data source also applies to the next two table rows of Rural and Urban) | Estimate of the resident population including all people currently residing in the United States. |
| Rural | Population residing in a rural area (as designated by the U.S. Census Bureau). | ||
| Urban | Population residing in an urban area (as designated by the U.S. Census Bureau). | ||
| Density | FCC 2021 Broadband Deployment Report (2019) (opens new window) | Population per square mile. | |
| Age (Over 65 Years) | County Health Rankings & Roadmaps program (2021) (opens new window) | Percentage of the population aged 65 and older according to the U.S. Census Population Estimates. | |
| Female | County Health Rankings & Roadmaps program (2021) (opens new window); U.S. Census Bureau County Population Totals: 2010-2019 (opens new window) (Note: this data source applies for both females and males) | Percentage of the population that identifies as female. | |
| Social & Economic Factors | Median Household Income | Small Area Income and Poverty Estimates (SAIPE) (opens new window) (2019) | Median household income is the income level at which half of households earn more, and half of the households earn less. |
| Unemployment | Bureau of Labor Statistics (opens new window) (2019) | Percentage of the civilian labor force (aged 16 and older) who are unemployed but seeking work. | |
| Education (Attended Some College) | American Community Survey (ACS), 5-Year Estimates (opens new window) (2015-2019) | Percentage of adults (aged 25-44) with some post-secondary education. |
Data Provider (Release/Access Year): U.S. Census Bureau
(2020) (opens new window); Robert Wood Johnson Foundation & University of Wisconsin Population Health Initiative County Health Rankings &
Roadmaps (2021) (opens new window); FCC 2021 Broadband Deployment Report (opens new window); FCC Staff Block Estimates (2020) (opens new window)