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Ranking Methods
The County Health Rankings are based on a model of population health including
- Health outcomes--based on measures of length and quality of life
- Health factors—based on a combination of measures of four major factors that influence health outcomes: behaviors, clinical care, social and economic factors, and the physical environment.
The process for choosing measures was guided by
- Review of the literature around the impact of various factors on health outcomes
- Ability for factors to be modified through community action
- Review of America's Health Rankings methodology and indicators
- Availability and reliability of indicators at the county level throughout the nation
- Analysis, and
- Feedback from a panel of technical experts
The Rankings are based on summary composite scores of individual measures. We use within-state z-scores (not ranks) to standardize each individual measure to the same scale. These z-scores are combined into summary composite scores using weights. We calculate and rank eight different summary composites:
1. Health Outcomes
2. Health Outcomes – Mortality
3. Health Outcomes – Morbidity
4. Health Factors
5. Health Factors – Health Behaviors
6. Health Factors – Clinical Care
7. Health Factors – Social and Economic Factors
8. Health Factors – Physical Environment
Health Outcome Summary Score
In calculating the summary score of the health outcomes in the County Health Rankings, the following weighting will be used, based on the subjective judgment that mortality and morbidity should be considered equally important in describing county health:
Health Outcome Weights for the 2010 County Health Rankings
| Outcome | Focus Area | Measure |
| Mortality (50%) | Premature death | Years of potential life lost before age 75 (50%) |
| Morbidity (50%) | Quality of life |
Percent reporting poor or fair health (10%)
Physically unhealthy days (10%)
Mentally unhealthy days (10%)
|
| Poor birth outcomes |
Low birthweight live births (20%) |
Within morbidity, we assign a higher weight to the low birthweight measure since this measure is based on a census of all live births whereas the other measures are based on a survey of a sample of the population.
Health Factors Summary Score
To calculate the summary score of health factors, weights were determined for each of the four major factors (health behaviors, clinical care, social and economic factors, and the physical environment) based on a review of the literature, expert opinion, and data analysis. The weights for specific measures were assigned based on relative importance within the factor and considerations of data reliability and availability. A table presenting the weights follows.
Health Factor Weights for the 2010 County Health Rankings
| Health Factor | Focus Area | Measure |
| Health behaviors (30%) | Smoking (10%) | Adult smoking rate (10%) |
| Diet and exercise (10%) | Adult obesity rate (10%) | |
| Alcohol use (5%) |
Binge drinking (2.5%)
Motor vehicle crash death rate (2.5%)
|
|
| Unsafe sex (5%) |
Chlamydia rate (2.5%)
Teen birth rate (2.5%)
|
|
| Clinical care (20%) | Access to care (10%) |
Adult uninsured rate (5%)
Primary care provider rate (5%)
|
| Quality of care (10%) |
Hospitalization rates for ambulatory-sensitive conditions (5%)
Diabetic screening rate (2.5%)
Hospice use rate (2.5%) |
|
| Social and economic factors (40%) | Education (10%) |
High school graduation rate (5%)
Adults with college degrees (5%)
|
| Employment (10%) | Unemployment rate (10%) | |
| Income (10%) |
Children in poverty (7.5%)
Income inequality (2.5%)
|
|
| Family and social support (5%) |
Social and emotional support (2.5%)
Single-parent households (2.5%)
|
|
| Community safety (5%) | Violent crime or homicide rate (5%) | |
| Physical Environment (10%) | Environmental quality (5%) |
Unhealthy air quality due to particulate matter (2.5%)
Unhealthy air quality due to ozone (2.5%)
|
| Built environment (5%) |
Access to healthy foods (2.5%)
Liquor store density (2.5%)
|
NOTE: Additional information is available about the measures in the Health Outcomes and Health Factors sections and about the methods used to determine these weights (Working Paper on Assigning Determinant Weights).
Other Methods Issues
Statistical Uncertainty
Within each of our county snapshots, we provide the margin of errors or 95% confidence intervals for the data that comprises our indicators. We also provide more detailed information that allows communities to see all counties' data for each particular indicator. Many county rates for specific indicators are not statistically different from one another, but when you combine them in a model with all the other indicators, those various measures produce the different rankings.
Data Reliability
Reliability depends on the specific measures. We provide background on the data for each of our measures. Mortality data, for example, are extremely reliable. Deaths are reported 100% of the time, and so the death rates are based on a "census", (i.e., all deaths that occurred rather than a sample of deaths), and are thus have high reliability. Other measures, for example, air quality and binge drinking, might be based on sampling methods, and so we provide more detailed background information to help users understand the quality of those measures. For example, although survey data are very useful, they have some well-known limitations. e.g., if they rely on the availability of land line telephones or when they involve self-reports with no way of determining if people respond and answer truthfully. However, when all of the measures are combined, we are confident that these measures provide a solid picture of overall health in a community and we have found in Wisconsin that the results are not surprising. The counties at the bottom of the list for overall health are counties that have had challenges for decades with respect to employment, income and education but also unhealthy behaviors and health care systems that are not in great shape. Looking measure by measure, there may be concerns about reliability but, overall, the summary message of overall health in a community comes through despite some of the data limitations.
Insufficient Data for Ranking
One hundred twenty-four counties or county-equivalents (e.g., in Alaska) were not ranked at all. For some additional counties, there will be some individual measures where there is not a large enough sample size to report data for a particular measure. In this situation, the overall rank of the county will not include the measures that had too small of a sample size.
Treatment of Missing Values
Counties had to have sufficient data for our key outcome measures to be ranked. For counties that were missing only a few measures, we assigned the state average for any missing measure in order to calculate a rank for that category.
Age-Adjustment of Measures
The following outcome measures are age adjusted: premature death (YPLL), self-reported health, physically unhealthy days, and mentally unhealthy days.
