Among the many measures used in public health research and practice, mortality data are among the most important. These data can offer crucial insights into the health of populations, including whether certain causes of death are becoming more or less common, and whether death rates and causes of death vary across demographic subgroups—a sign of health inequities.
However, one limitation of standard mortality data is that they treat each death as mathematically identical, whether an individual died at age 5 or age 105. While every human life lost is tragic, deaths that occur at a relatively young age can offer us particular insights into public health. A person who dies at age 105 has exceeded U.S. life expectancy (74.8 for males and 75.8 for females in 2023), whereas a person who dies at age 5 has fallen short of their life expectancy by several decades.
Measures of premature death are designed to address that limitation in mortality data by quantifying the gap in number of years between age of death and life expectancy among people who die before reaching life expectancy age.
On SHADAC’s State Health Compare website, we offer a measure called “premature deaths,” which estimates the number of years of potential life lost prior to age 75 (an approximation of U.S. life expectancy) per 100,000 people.
Calculating Years of Potential Life Lost
SHADAC’S State Health Compare (SHC) measures premature death by the number of years of potential life lost (YPLL) per 100,000 people, using data from the CDC’s Web-based Injury Statistics Query and Reporting System (WISQARS).
Let’s break that definition down.
YPLL is calculated by subtracting the age at death from a standard or “expected” age of death. For example, State Health Compare uses 75 as the standard age of death, meaning that it assumes those who die before age 75 (roughly the U.S. life expectancy) to have died prematurely. So, if someone died at age 35, this would account for 40 YPLL.
Let’s look at this general calculation below.
Years of potential life lost (YPLL) = Standard/Base Age – Age at Death
YPLL = 75 years – 35 years
YPLL = 40
To get the total YPLL for each state or group, individual YPLL values for each cause of death are summed.
SHADAC’s measure uses age-adjusted years of potential life lost (AA YPLL). This is done because mortality risk is closely related to age, but the age distribution of populations can vary.
For instance, some states in the U.S. lean younger than other states, and the age distribution of states also changes over time. By using age-adjusted estimates of YPLL, we can better compare estimates of YPLL across different populations, or even in the same population over time.
We report YPLL estimates as a rate of “number of years of potential life lost (e.g., 7,000 years) per 100,000 people,” which is also done to facilitate comparison of different populations, or the same population over time (since population sizes differ and change over time).
Strengths and Limitations of YPLL
One of the most important strengths of YPLL as a public health measure is that, by virtue of focusing on mortality among younger people (i.e., less than life expectancy), many of the associated deaths stem from preventable causes.
For instance, unintentional injuries (e.g., automobile collisions) are a top cause of death in U.S. children. Additionally, because YPLL focuses on deaths that occur before life expectancy (roughly, using an age of 75), this measure highlights where public health efforts could have the greatest impact on extending lives and increasing life expectancy.
YPLL also can be particularly a useful, and unique, way to identify and quantify health disparities that may be less apparent in mortality data, particularly when it comes to understanding the impacts of deaths among children and young adults. That is because deaths among children and young adults are relatively rare, but YPLL underscores their heavy toll in years of lost life.
Additionally, YPLL hints at broader economic and social impacts of premature death, including unrealized economic productivity, loss of social relationships and community contributions, and other forgone benefits.
However, YPLL also has important limitations that researchers and policymakers should consider. For instance, population-level data on YPLL can mask variations within communities, such as the disparities we see by race and ethnicity, gender, and geography. This limitation underscores the importance of disaggregating estimates by race/ethnicity and other demographic characteristics, which SHADAC researchers do on SHC to illuminate health disparities.