| Documentation: | Health Data 2020 Release |
| Document: | Health Data: Technical Documentation |
| citation: | Social Explorer; Health Data 2015: Technical Documentation |
The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based random digit dial (RDD) telephone survey that is conducted annually in all states, the District of Columbia, and U.S. territories. Data obtained from the BRFSS are representative of each state's total non-institutionalized population over 18 years of age and has included more than 400,000 annual respondents with landline telephones or cellphones since 2011. Data are weighted using iterative proportional fitting (also called "raking") methods to reflect population distributions. For the County Health Rankings, data from the BRFSS are used to measure various health behaviors and health-related quality of life (HRQoL) indicators. HRQoL measures are age-adjusted to the 2000 U.S. standard population.
Prior to the 2020 County Health Rankings, up to seven survey years of landline only BRFSS data were aggregated to produce county estimates. However, even with multiple years of data, these did not provide reliable estimates for all counties, particularly those with smaller respondent samples.
For the 2020 County Health Rankings, the CDC produced 2014 county estimates using single-year 2014 BRFSS data and a multilevel modeling approach based on respondent answers and their age, sex and race/ethnicity, combined with county-level poverty and county and state level contextual effects (1).
To produce estimates for those counties where there was no or limited data, the modeling approach borrowed information from the entire BRFSS sample as well as Census Vintage 2014 population estimates. CDC used a parametric bootstrapping method to produce standard errors and confidence intervals for those point estimates. This estimation methodology was validated for all U.S. counties, including those with no or small (<50 respondents) samples (2).
One limitation of the BRFSS is that all measures are based on self-reported information, which cannot be validated with medical records. Another limitation is that these model-based estimates were created by borrowing information from the entire BRFSS, which may or may not accurately reflect those counties’ local intervention experiences. Additionally, the confidence intervals constructed from these methods appear much smaller than confidence intervals reported for direct survey methods in previous years.
This measure is based on survey responses to the question: "Thinking about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good?" The value reported in the County Health Rankings is the average number of days a county's adult respondents report that their physical health was not good. The measure is age-adjusted to the 2000 US population.
This measure is based on survey responses to the question: "Thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?" The value reported in the County Health Rankings is the average number of days a county's adult respondents report that their mental health was not good. The measure is age-adjusted to the 2000 US population.
The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based random digit dial (RDD) telephone survey that is conducted annually in all states, the District of Columbia, and U.S. territories. Data obtained from the BRFSS are representative of each state's total non-institutionalized population over 18 years of age and has included more than 400,000 annual respondents with landline telephones or cellphones since 2011. Data are weighted using iterative proportional fitting (also called "raking") methods to reflect population distributions. For the County Health Rankings, data from the BRFSS are used to measure various health behaviors and health-related quality of life (HRQoL) indicators. HRQoL measures are age-adjusted to the 2000 U.S. standard population.
Prior to the 2020 County Health Rankings, up to seven survey years of landline only BRFSS data were aggregated to produce county estimates. However, even with multiple years of data, these did not provide reliable estimates for all counties, particularly those with smaller respondent samples.
For the 2020 County Health Rankings, the CDC produced 2014 county estimates using single-year 2014 BRFSS data and a multilevel modeling approach based on respondent answers and their age, sex and race/ethnicity, combined with county-level poverty and county and state level contextual effects (1).
To produce estimates for those counties where there was no or limited data, the modeling approach borrowed information from the entire BRFSS sample as well as Census Vintage 2014 population estimates. CDC used a parametric bootstrapping method to produce standard errors and confidence intervals for those point estimates. This estimation methodology was validated for all U.S. counties, including those with no or small (<50 respondents) samples (2).
One limitation of the BRFSS is that all measures are based on self-reported information, which cannot be validated with medical records. Another limitation is that these model-based estimates were created by borrowing information from the entire BRFSS, which may or may not accurately reflect those counties’ local intervention experiences. Additionally, the confidence intervals constructed from these methods appear much smaller than confidence intervals reported for direct survey methods in previous years.
Self-reported health status is a general measure of health-related quality of life (HRQoL) in a population. This measure is based on survey responses to the question: "In general, would you say that your health is excellent, very good, good, fair, or poor?" The value reported in the County Health Rankings is the percentage of adult respondents who rate their health "fair" or "poor". The measure is age-adjusted to the 2000 US population. Respondents were adults (age 18 and more).
Low Birthweight is the percentage of live births where the infant weighed less than 2,500 grams (approximately 5 lbs., 8 oz.). Low birthweight (LBW) represents two factors: maternal exposure to health risks and an infant's current and future morbidity, as well as premature mortality risk. From the perspective of maternal health outcomes, LBW indicates maternal exposure to health risks in all categories of health factors, including her health behaviors, access to health care, the social and economic environment she inhabits, and environmental risks to which she is exposed. In terms of the infant's health outcomes, LBW serves as a predictor of premature mortality and/or morbidity over the life course and for potential cognitive development problems.
Primary care physicians include practicing physicians (M.D.'s) specializing in general practice medicine, family medicine, internal medicine, pediatrics, and obstetrics/gynecology. The measure represents the number of primary care physicians and the rate of primary care physicians per 100,000 population. Access to care requires not only financial coverage, but also, access to providers.
Mental health providers include psychiatrists, psychologists, licensed clinical social workers, counselors, and advanced practice nurses who specialize in mental health care. The measure represents the number of mental health providers and rate of mental health providers per 100,000 population.
Persons without Insurance (Population under 65, 2013 est.) represents the percentage and the number of the population under age 65 that has no health insurance coverage. The Small Area Health Insurance Estimates uses the American Community Survey (ACS) definition of insured: Is this person CURRENTLY covered by any of the following types of health insurance or health coverage plans: Insurance through a current or former employer or union, insurance purchased directly from an insurance company, Medicare, Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low incomes or a disability, TRICARE or other military health care, Indian Health Services, VA or any other type of health insurance or health coverage plan?
Persons without Insurance (Population under 19 Years, 2013 est.) represents the percentage and the number of the population under age 19 that has no health insurance coverage. The Small Area Health Insurance Estimates uses the American Community Survey (ACS) definition of insured: Is this person CURRENTLY covered by any of the following types of health insurance or health coverage plans: Insurance through a current or former employer or union, insurance purchased directly from an insurance company, Medicare, Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low incomes or a disability, TRICARE or other military health care, Indian Health Services, VA or any other type of health insurance or health coverage plan?
Persons without Insurance (Population 18 to 64 Years, 2013 est.) represents the percentage and the number of the population ages 18 to 64 that has no health insurance coverage in a given county. The Small Area Health Insurance Estimates uses the American Community Survey (ACS) definition of insured: Is this person CURRENTLY covered by any of the following types of health insurance or health coverage plans: Insurance through a current or former employer or union, insurance purchased directly from an insurance company, Medicare, Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low incomes or a disability, TRICARE or other military health care, Indian Health Services, VA or any other type of health insurance or health coverage plan?
Premature Deaths (Less Than 75 Years) is the number of deaths under age 75. Measuring premature mortality, rather than overall mortality, reflects the County Health Rankings' intent to focus attention on deaths that could have been prevented.
Years of Potential Life Lost (YPLL) is the years of potential life lost before age 75 (YPLL-75). Every death occurring before the age of 75 contributes to the total number of years of potential life lost. For example, a person dying at age 25 contributes 50 years of life lost, whereas a person who dies at age 65 contributes 10 years of life lost to a county's YPLL. The YPLL measure is presented as a rate per 100,000 population and is age-adjusted to the 2000 US population.
Infant mortality measures the number of deaths among children less than one year of age per 1,000 live births. Infant mortality represents the health of the most vulnerable age group (those under 365 days). Understanding the child mortality rate in a county can help interpret the years of potential life lost (YPLL) rate. We provide both the infant mortality rate and the number of infant deaths.
Child Mortality is the number of deaths among children under age 18 per 100,000 population. Understanding the child mortality rate in a county can help interpret the years of potential life lost (YPLL) rate. We provide both the child mortality rate and the number of child deaths.
Premature age-adjusted mortality measures the number of deaths among residents under the age of 75 per 100,000 population. Premature age-adjusted mortality is a common and important population health outcome measure. We provide both the premature age-adjusted mortality rate and the number of premature age-adjusted deaths.
Drug Poisoning Mortality represents the number of drug poisoning deaths per 100,000 population. We provide both the drug poisoning mortality rate and the number of drug poisoning deaths. This measure includes accidental, intentional, and of undetermined poisoning by and exposure to:
Diabetics is the prevalence of diagnosed diabetes in a given county. Respondents were considered to have diagnosed diabetes if they responded "yes" to the question, "Has a doctor ever told you that you have diabetes?" Women who indicated that they only had diabetes during pregnancy were not considered to have diabetes.
Teen Births are the number of births per 1,000 female population, ages 15-19 and this measure is associated with unsafe sexual activity. Teen birth data are readily available and reliable for nearly all counties. We provided both the number of births and birth rates per 100,000 females aged 15 - 19.
Sexually Transmitted Infections (STI) are measured as the chlamydia incidence (number of new cases reported) per 100,000 population. We provided both the rate of Chlamydia cases per 100,000 population and the number of Chlamydia cases.
HIV prevalence measures the number of diagnosed cases of HIV in a county per 100,000 population. HIV is an important marker for a range of risky health behaviors. The County Health Rankings use disease-specific measures for ranking calculations only when no other reliable source for risk factor or outcome data is available. We provided both the HIV prevalence rate per 100,000 population and the number of HIV cases.
Adult Smoking is the percentage of the adult population that currently smokes every day or most days and has smoked at least 100 cigarettes in their lifetime.
Excessive Drinking is the percentage of adults that report either binge drinking, defined as consuming more than 4 (women) or 5 (men) alcoholic beverages on a single occasion in the past 30 days, or heavy drinking, defined as drinking more than one (women) or 2 (men) drinks per day on average.
Limited Access to Healthy Foods is the percentage of the population who are low income and do not live close to a grocery store. Living close to a grocery store is defined differently in rural and nonrural areas; in rural areas, it means living less than 10 miles from a grocery store; in nonrural areas, less than 1 mile. Low income is defined as having an annual family income of less than or equal to 200 percent of the federal poverty threshold for the family size.
Percentage of population with adequate access to locations for physical activity. Access to Exercise Opportunities measures the percentage of individuals in a county who live reasonably close to a location for physical activity. Locations for physical activity are defined as parks or recreational facilities. Parks include local, state, and national parks. Recreational facilities include businesses identified by the following Standard Industry Classification (SIC) codes and include a wide variety of facilities including gyms, community centers, YMCAs, dance studios and pools.
Adult Obesity is the percentage of the adult population (age 20 and older) that reports a body mass index (BMI) greater than or equal to 30 kg/m2. Obesity is often the result of an overall energy imbalance due to poor diet and limited physical activity. Obesity increases the risk for health conditions such as coronary heart disease, type 2 diabetes, cancer, hypertension, dyslipidemia, stroke, liver and gallbladder disease, sleep apnea and respiratory problems, osteoarthritis, and poor health status.
Physical Inactivity is the percentage of adults aged 20 and over reporting no leisure-time physical activity. Examples of physical activities provided include running, calisthenics, golf, gardening, or walking for exercise.
The Food Environment Index ranges from 0 (worst) to 10 (best) and equally weights two indicators of the food environment: Limited access to healthy foods and Food insecurity.
Air Pollution measures the particulate matter in the air. It reports the average daily density of fine particulate matter in micrograms per cubic meter. Fine particulate matter is defined as particles of air pollutants with an aerodynamic diameter less than 2.5 micrometers (PM2.5).From EPHT: The monitoring data comes from the U.S. Environmental Protection Agency's (EPA) Air Quality System (AQS). When AQS data are available from multiple monitors for a given county and day, the highest 24-h average (daily) PM2.5 concentration among all the monitors is selected for purposes of creating daily county level data. EPA provides modeled estimates of PM2.5 using Downscaler (DS) model, which uses a statistical approach to fuse monitoring data in areas where monitors exist, and relies on Community Multiscale Air Quality (CMAQ) modeled output in areas without monitors. DS modeled estimates are available by census tract centroid-the geographic center of the census tract. Daily county-level modeled estimates are obtained by selecting the maximum value observed among all the census tracts within each county. County-level PM2.5 measures are created using monitor data when available and using modeled estimates for days and locations without such data. The model is intended to model the level of pollutants in the layer of atmosphere that we are breathing as we assume that the pollutants are equally distributed across the county.While this measure estimates the average annual concentration of fine particulate pollution in the county, it can miss important short-term fluctuations in air quality (such as stagnation events), local patterns (high concentrations near roads and other major sources), and other pollutants (such as ozone, etc.).
Drinking Water Violations has only two values: Yes and No. A “Yes” indicates that at least one community water system in the county received at least one health-based violation during the specified time frame. A “No” indicates that there were no health-based drinking water violations in any community drinking water system in the county. Health-based violations include Maximum Contaminant Level, Maximum Residual Disinfectant Level, and Treatment Technique violations.
Severe Housing Problems is the percentage of households with one or more of the following housing problems:
Driving Alone to Work is the percentage of the workforce that usually drives alone to work. The numerator is the number of workers who commute alone to work via car, truck, or van. The denominator is the total workforce.
Long Commute - Driving Alone is the percentage of workers who drive alone with a commute longer than 30 minutes. The numerator is the number of workers who drive alone (via car, truck, or van) for more than 30 minutes during their commute. The denominator is the number of workers who drive alone (via car, truck, or van) during their commute.
