Institute for Health Metrics and Evaluation
NIH Collaboration Seeks to Help Understand U.S. Burden of Health Disparities: Why Your County Matters
Posted on by Eliseo J. Pérez-Stable, M.D., National Institute on Minority Health and Health Disparities
Since the early 1990s, federal support of research has increased to understand minority health and identify and address health disparities. Research in these areas has evolved from a starting point of developing a basic descriptive understanding of health disparities and who is most affected. Now, it is discovering the underlying complexity of factors involved in health outcomes to inform interventions and reduce these disparities.
One of these many factors is where we live, learn, work, and play and how that affects different people. A group of NIH scientists and their colleagues recently published a study in the journal The Lancet that they hope is a step toward better understanding geographic disparities and their role in health equity [1].
As Director of NIH’s National Institute on Minority Health and Health Disparities (NIMHD), I worked with NIMHD’s Scientific Director, Anna María Nápoles, to conceive the study and establish the Global Burden of Disease (GBD) U.S. Health Disparities Collaborators at NIH with five NIH Institutes and two Offices. Through this collaboration, NIH funded the Institute for Health Metrics and Evaluation (IHME), University of Washington to conduct the analysis. The IHME has worked for 30 years on the GBD project in over 200 countries.
The Lancet paper offered the first comprehensive U.S. county-level life expectancy estimates to highlight the significant gaps that persist among racial and ethnic populations across the nation. The analysis revealed that despite overall life expectancy gains of 2.3 years from 2000–2019, Black populations experienced shorter life expectancy than White populations.
In addition, American Indian and Alaska Native populations’ life expectancy did not improve and, in fact, decreased in most counties. We found national-level life expectancy advantages for Hispanic/Latino and Asian populations ranging from three to seven years, respectively, compared to White populations. But there were notable exceptions for Hispanic/Latino populations in selected counties in the Southwest.
Certainly the most-alarming trend identified in the paper was that during the study’s last 10 years (2010–2019), life expectancy growth was stagnant across all races and ethnicities. Moreover, 60 percent of U.S. counties experienced a decrease in life expectancy.
While these findings provide an important frame for how disparities exist along many dimensions—by race, ethnicity, and geographic region—they also highlight these differences within our local communities. This level of detail offers an unprecedented opportunity for researchers and public health leaders to focus on where these differences are the most prominent, and possibly give us a clearer picture on what can be done about it.
These data raise many important questions, too. What can we learn from places that are doing well in caring for their most disadvantaged populations? How can these factors be sustained, replicated, and transferred to other places? Are there current policies and/or community services that contribute to or inhibit gaining access to appropriate clinical care, healthy and affordable food, good schools, and/or economic opportunities?
To help answer these questions, the GBD U.S. Health Disparities Collaborators at NIH, in partnership with IHME, have developed a comprehensive database and interactive data visualization tool that provides life expectancy and all-cause mortality by race and ethnicity for 3,110 U.S. counties from 2000-2019. Efforts are underway to expand the database to include causes of death and risk factors by race/ethnicity and education, as well as to disaggregate some of the major racial-ethnic groups.
Using IHME’s established model of comprehensive and replicable data collection, the joint effort aims to improve access to health data resources, bolster analytic approaches, and deliver user-friendly estimates to the wider research and health policy community. The collection’s standardized, comprehensive, historical, and real-time data can be the cornerstone for efforts to address disparities and advance health equity.
It is important to note that the Lancet study only included data from before the COVID-19 pandemic. The pandemic’s disproportionate effect on overall mortality and life expectancy has exacerbated existing health disparities. Disaggregated data are essential in helping to understand the underlying mechanisms of health disparities and guiding the development and implementation of interventions that address local needs.
As a clinician scientist, I have made a personal commitment at NIMHD to foster and encourage data collection with standardized measures, harmonization, and efficient data sharing to help us explore the nuances within all populations and their communities. Without these guiding principles for managing data, inequities remain unseen and unaddressed. Scientists, clinicians, and policymakers can all potentially benefit from this work if we use the data to inform our actions. It is an opportunity to implement real change in our NIH-wide combined efforts to reduce health disparities and improve quality of life and longevity for all populations.
Reference:
[1] Life expectancy by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities. GBD US Health Disparities Collaborators. Lancet. 2022 Jul 2;400(10345):25-38.
Links:
Understand Health Disparities Series (National Institute on Minority Health and Health Disparities/NIH)
HD Pulse (NIMHD)
PhenX Social Determinants of Health Toolkit (NIMHD)
Institute for Health Metrics (University of Washington, Seattle)
NIH Support: The members of the GBD U.S. Health Disparities Collaborators at NIH include: National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; NIH Office of Disease Prevention; NIH Office of Behavioral and Social Science Research
Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes and Centers (ICs) to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 17th in the series of NIH IC guest posts that will run until a new permanent NIH director is in place.
Masks Save Lives
Posted on by Dr. Francis Collins
Reminding others that “masks save lives” isn’t just sound advice. It’s a scientific fact that wearing one in public can help to slow the spread of SARS-CoV-2, the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic.
I’m very careful to wear a mask outside my home whenever I’m out and about. I do it not necessarily to protect myself, but to protect others. If by chance I’ve been exposed to the virus and am currently incubating it, I wouldn’t want to spread it to other people. And any of us could be an unknowing superspreader. We owe it to everyone we encounter, especially those who are more vulnerable, to protect them. As my NIH colleague Tony Fauci recently demonstrated, it’s possible to wear your mask even while you’re outside exercising.
But there are still skeptics around. So, just how much does a facial covering protect those around you? Quite a bit, according to researchers who created a sophisticated mathematical model to take a more detailed look [1]. Their model shows that even if a community universally adopted a crude cloth covering that’s far less than 100 percent protective against the virus, this measure alone could significantly help to reduce deaths.
These findings, funded partly by NIH, were published recently in Nature Communications. They come from Colin Worby, Broad Institute of MIT and Harvard, Cambridge, MA, and Hsiao-Han Chang, National Tsing Hua University, Taiwan.
The researchers noted several months ago that recommendations on wearing a mask varied across the United States and around the world. To help guide policymakers, the researchers simulated outbreaks in a closed, randomly interacting population in which the supply and effectiveness of crude cloth or disposable, medical-grade masks varied.
Under different outbreak scenarios and mask usages, the researchers calculated the total numbers of expected SARS-CoV-2 infections and deaths from COVID-19. Not surprisingly, they found that the total number of deaths and infections declined as the availability and effectiveness of face masks increased.
The researchers’ model primarily considered the distribution of medical-grade, surgical masks. But because such masks are currently available in limited supply, they must be prioritized for use by health care workers and others at high risk. The researchers go on to note that the World Health Organization and others now recommend wearing homemade face coverings in public, especially in places where the virus is spreading. While it’s true the ability of these face coverings to contain the virus is more limited than medical-grade masks, they can help and will lead to many fewer deaths.
Another recent paper also suggests that while wearing a mask is primarily intended to prevent the wearer from infecting others, it may also help lower the dose, or inoculum, of SARS-CoV-2 that the wearer might receive from others, resulting in milder or asymptomatic infections [2]. If correct, that’s another great reason to wear a mask.
Already, more than 175,000 people in the United States have died from COVID-19. The latest estimates [3] from the Institute for Health Metrics and Evaluation (IHME) at the University of Washington’s School of Medicine, Seattle, predict that the COVID-19 death toll in the U.S. may reach nearly 300,000 by December 1.
But that doesn’t have to happen. As this new study shows, face coverings—even those that are far from perfect—really can and do save lives. In fact, IHME data also show that consistent mask-wearing—starting today—could save close to 70,000 lives in the months to come. Saving those lives is up to all of us. Don’t leave home without your mask.
References:
[1] Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic. Worby CJ, Chang HH. Nat Commun. 2020 Aug 13;11(1):4049.
[2] Masks Do More Than Protect Others During COVID-19: Reducing the Inoculum of SARS-CoV-2 to Protect the Wearer. Gandhi M, Beyrer C, Goosby E. J Gen Intern Med. 2020 Jul 31.
[3] New IHME COVID-19 forecasts see nearly 300,000 deaths by December 1. Institute for Health Metrics and Evaluation. August 6, 2020.
Links:
Coronavirus (COVID-19) (NIH)
Colin Worby (Broad Institute of MIT and Harvard, Cambridge, MA)
Hsiao-Han Chang (National Tsing Hua University, Taiwan)
NIH Support: National Institute of Allergy and Infectious Diseases
