A New View of Life Expectancy

Do you know what life expectancy is where you live? A new, first-of-its-kind map from the National Center for Health Statistics (NCHS) lets you explore detailed life expectancy estimates across the United States, down to the census tract level.

While there have been other tools to help users find this information, the new map provides a truly interactive experience that lets people discover, compare, and work with the data in a visual format.

Capturing health at a more local level

Life Expectancy at Birth for US Census Tracts, 2010-2015

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 “I think the true greatness of the map lies in the data themselves,” says Betzaida Tejada-Vera, the statistician managing the visualization’s development.

The data shown by the map come from the U.S. Small-area Life Expectancy Estimates Project (USALEEP), which shed new light on the health of our nation by calculating life expectancy estimates for almost 70,000 individual U.S. census tracts, covering all 50 states and Washington D.C. This project was a unique collaboration among NCHS, the National Association for Public Health Statistics and Information Systems, and the Robert Wood Johnson Foundation.

USALEEP estimates provided our most granular look to date at the disparities that can exist between people living in the same areas. Results showed for the first time how county-level data may not be enough to capture health inequalities between our communities.

“Health delivery happens at the local level, and things about the local environment impact our health,” notes DVS Deputy Director Paul Sutton, who guided the project from its inception. “However, not every system can report at that level. Vital records are unique in their ability to give us this information.” 

An ambitious undertaking

The new map makes a huge leap in how we can interact with these groundbreaking data. But creating such a detailed visualization required a lot of planning – and a lot of innovative problem solving – on the part of DVS’ statisticians and web developers.

From the outset of the project, the team set ambitious goals. They wanted to create a multi-level map with a “layered” design. The visualization would also have to be 100% interactive; contain all census tracts; be intuitive, useful, and responsive; be web-browser stable; and be updatable.

As the they tackled the project, the team uncovered some unique challenges, including the need to seek out alternative data visualization tools to handle a map with such large datasets. The layered map design also includes state-level data, making the information even more complicated to put together in one place.

Statistician Brigham Bastian notes the difficulty they faced in finding the right technologies. “A lot of our usual tools were not able to handle the complexity and scope of the project. We would try different methods and the visualization would crash, over and over.” 

Bigger data demands innovative solutions

With their usual tools buckling under the weight of all the data, DVS experts finally landed on D3.js as the solution. “This data visualization library works well with large datasets, provides complete control over the visualization, offers customization, and is fast and highly responsive,” says Brian Salant, Sr. Data Visualization Analyst from MirLogic Solutions.

The team spent many months hammering out the bugs and getting the flow just right – deciding what users might be looking for and how they might want to find it, adding new features, and smoothing out the interface.

The result? An innovative and fully interactive map that allows users to zoom in and out, look broadly or specifically across areas, keep a log of their findings, and make comparisons at the state and census-tract levels. 

An evolving tool for public health

 “A great deal of dedication, expertise, and passion for public health data went into the creation and completion of this unprecedented project,” says Arias.

But the work does not stop here. Plans for future updates to the map include additions of county-level estimates, plug-in capability, and geographic references like interstate roads, forests, and bodies of water.

In the end, the map will serve as a comprehensive tool to access information that matters deeply to public health. “Part of the reason we undertook this project was that it helped us move forward with getting better death data at a local level,” says Sutton. “Advancing our ability to geocode data and understand death rates by cause for smaller geographic areas is hugely valuable to what we can do in the future.”

Being able to examine mortality data in new ways can provide a springboard for research and decisions that create healthier, longer lives for everyone – no matter where they live. to support healthier, more equitable communities.

“Seeing tens of thousands of estimates take form visually conveys their meaning in ways impossible to do otherwise,” says Elizabeth Arias, Director of the US Life Table Program in NCHS’ Division of Vital Statistics (DVS), who led production of the census tract estimates.