Premature Age-Adjusted Mortality*
In the model
Use County Health Rankings’ model of health to explore the measures that influence how long and how well we live.
Number of deaths among residents under age 75 per 100,000 population (age-adjusted). The 2022 County Health Rankings used data from 2018-2020 for this measure.
Premature Age-Adjusted Mortality is a common and important population health outcome measure.
Data and methods
National Center for Health Statistics - Mortality Files
Data on deaths and births were provided by NCHS and drawn from the National Vital Statistics System (NVSS). These data are submitted to the NVSS by the vital registration systems operated in the jurisdictions legally responsible for registering vital events (i.e., births, deaths, marriages, divorces, and fetal deaths). In prior years of the Rankings, Premature Death was calculated by the National Center for Health Statistics, but this year the Mortality-All County (micro-data) file was requested. This allowed us to calculate Premature Death and Life Expectancy ourselves. While most calculations of mortality rates can be downloaded from CDC WONDER, the calculation of Years of Potential Life Lost and Life Expectancy requires raw data files.
Key Measure Methods
Premature Age-Adjusted Mortality is a rate
Premature Age-Adjusted Mortality measures the number of deaths among residents under the age of 75 per 100,000 population. Rates measure the number of events (e.g., deaths, births) in a given time period (generally one or more years) divided by the average number of people at risk during that period. Rates facilitate data comparisons across counties with different population sizes.
Premature Age-Adjusted Mortality is age-adjusted
Age is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. We report an age-adjusted rate in order to fairly compare counties with differing age structures.
Premature Age-Adjusted Mortality is a rare event (statistically speaking)
Premature death is a relatively rare event in most counties. Counties with smaller populations can see a lot of change in their premature death rates from year to year. Such changes are usually due to normal variation and are not necessarily caused by any actual change in the underlying risk of premature death in the county. To help determine if the change in premature death rate in a county is due to normal variation or actual change in community experience, we recommend examining the provided error margins. Error margins are statistical tools that can aid interpretation of variation in measures. If the error margins overlap year to year, it’s less likely that the variation in premature death reflects real underlying changes.
What deaths count toward Premature Age-Adjusted Mortality?
Deaths are counted in the county where the individual lived. So, even if an individual dies in a car crash on the other side of the state, the death is attributed to the individual's county of residence.
Some data are suppressed
A missing value is reported for counties with fewer than 20 premature deaths in the time frame.
The numerator is the number of total deaths under the age of 75.
The denominator is the total population under the age of 75.
Can This Measure Be Used to Track Progress
This measure can be used to measure progress with some caveats. Premature mortality is a long-term health outcome, effects of interventions might not be reflected in this measure for years or even decades after a program or policy is implemented. Premature death is also a relatively rare event, especially in small counties. Statistics depend on large numbers of events to detect small changes, meaning that small changes in small communities may be difficult to detect. Lastly, it is important to note that the estimate provided in the County Health Rankings is a 3-year average.
Finding More Data
Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:
We recommend starting with the CDC Wonder database, which contains information on death rates by race, ethnicity, age, gender, geography, cause of death, and more. Rates can be exported as crude or age-adjusted. Small counties might need to combine multiple years of data to see rates, as CDC suppresses any rates when there are fewer than 10 deaths.
You can also use the County Health Rankings’ Mortality and Life Expectancy Calculator if you have information on the population and deaths in the geography of interest to calculate Premature Age-Adjusted Mortality.