NIMHD Hosts Workshop on U.S. Global Burden of Disease

Dr. Christopher Murray, professor and chair of health metrics sciences and director of IHME, presented the results of the GBD 2021 report with topics that included life expectancy, cause-specific mortality and disease risk factor comparisons across countries. Dr. Laura Dwyer-Lindgren, associate professor of health metrics sciences at IHME, discussed the GBD project. Dr. Ali Mokdad, professor of health metrics sciences at IHME, ran a workshop on how to use the GBD data. Dr. Joseph Dieleman, associate professor of health metrics sciences at IHME, presented on health care spending within the U.S.

Highlights of the presentations included that between 2000-2019:

• The U.S. ranked among the lowest in life expectancy compared to other high-income countries.
• Among racial and ethnic minority populations, American Indian and Alaska Native (AIAN) and Black populations had the lowest life expectancy, while Asian and Latino populations had the highest life expectancy. The White population had intermediate life expectancy: higher than life expectancy among AIAN and Black populations but lower than life expectancy among Latino and Asian populations.
• For most causes of death, mortality rates were highest for AIAN and Black populations and lowest for Asian and Latino populations. However, the size of the disparity, and the trends over time, varied considerably among causes.
• By geography, regardless of race and ethnicity, a huge disparity of up to 27 years difference in life expectancy was found across counties, with the lowest life expectancy at 65 years and highest at 92 years.
• Counties in certain regions (e.g., Southeast, Appalachia, Four Corners) had relatively poor outcomes across a wide range of metrics, including life expectancy and cause-specific mortality.
• Racial and ethnic disparities in life expectancy and cause-specific mortality observed nationally were also found in nearly all counties.

The GBD project is a systematic, scientific effort to quantify the magnitude of major diseases, risk factors and clinical outcomes by age, sex, race, ethnicity and geography over time. It uses available national data to create small area estimation models and tools to produce a comprehensive, comparable picture of all forms of health outcomes (diseases, injuries, impairments) so that health systems can be improved to reduce health disparities. The GBD project also uses predictive models to forecast future disease and health scenarios.

Speaking on the observed disparities, Dwyer-Lindgren noted that health disparities are the norm, not the exception, across geography, race and ethnicity in the U.S. and that the size of the disparities are large, even on a global scale. This theme resonated across several presentations. Nevertheless, the findings present opportunities that policymakers can leverage to drive policy decisions to reduce health disparities and achieve health equity.

“Achieving equity in health also entails tracking health care spending to determine where health care dollars come from, where it goes and who it serves,” said Dieleman. He noted vast disparities across geography, race and ethnicity in U.S. health care spending between 2010-2019, with higher personal health care spending in places with more income.

Preliminary estimates showed health care spending was lowest for racial and ethnic minority populations compared to the White population: in 2019, 76.2% of total U.S. health care spending was by the White population, while the AIAN population had the lowest health care spending at 0.7%.

Further framing the conversation around health disparities and the economics of health care, NIMHD Director Dr. Eliseo J. Pérez-Stable added, “the issue of health care spending is an important and critical conversation to have because it contributes to health disparities and outcomes based on the way the United States leverages the percentage of gross domestic product it spends on health, which is more than any other high-income country but with much worse outcomes.”

GBD data on health care spending can help policymakers understand where resources are being directed and who is benefiting, whether at the county, state or national level, and how disparities in health care spending are shifting over time. Additionally, the data can help to reduce inefficiencies in health care spending at the population level.

The U.S. GBD project continues to furnish updates on diseases, injuries and risk factors, which policymakers can use to prioritize interventions to improve health and save lives. Donors, researchers and the public also can use the data and forecasts to assess the impact of new policies, interventions or technologies on health. 

The workshop was organized by the NIMHD-led U.S. Health Disparities GBD working group at NIH (comprising researchers from the National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research), in partnership with IHME.