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HOST: The Healthy People initiative was launched by the U.S. Department of Health and Human Services over 40 years ago.  Healthy People provides science-based, 10-year targets for public health objectives for the U.S. population. As in the preceding two decades, Healthy People 2020, or HP2020, included an overarching goal related to health disparities.

On November 14, NCHS released a new report that examines changes in health disparities over time by race and ethnicity for HP2020 objectives, using three different measures of disparity. Data were analyzed for 506 objectives from 68 data sources from 2001 to 2018. The analyses were restricted to HP2020 objectives with data by race and ethnicity at the baseline and final timepoints for a minimum set of population groups.

Health disparities by race and ethnicity were evaluated using three measures that were used in HP2020: the maximal rate difference, maximal rate ratio, and summary rate ratio. Changes in disparities over time were evaluated by comparing the baseline and final timepoints for each of those respective measures.

Joining us today to talk about this new report is David Huang, chief of the Health Promotions Statistics Branch within the Division of Analysis and Epidemiology at NCHS:

HOST: Could you give us a little background on the Healthy People initiative?

DAVID HUANG: Sure.  Healthy People was established in 1979 and is a science-based, 10 year national initiative for improving the health of all Americans based on the latest available scientific evidence. At its core, Healthy People provides a strategic framework for a national prevention agenda that communicates a vision for improving health and achieving health equity. But at the heart of the initiative are the science-based measurable objectives with targets to be achieved by the end of each decade. We’re actually now in our fifth decade of the initiative, Healthy People 2030. And the Department of Health and Human Services, or HHS, leads the initiative through the Office of the Assistant Secretary for Health Office of Disease Prevention and Health Promotion, or ODPHP and NCHS serves as the statistical advisor to the initiative and has done so since the first iteration of healthy people.

HOST:  Now this month you’ve released a fairly comprehensive report on healthy People 2020. What are the main takeaways from this report?

DAVID HUANG: So this is a report that focuses on disparities, and we have a couple of primary takeaways. First, we found that health disparities by race and ethnicity generally changed very little over the past decade, and this was using 3 measures of health disparities across 68 different data sources and more than 500 objectives. The three measures we used were the maximal rate difference, the maximal rate ratio, and the summary rate ratio, and these measures represent absolute and relative, most and least favorable comparisons, as well as a summary measure that’s a relative measure. All of these measures have been used individually in multiple Healthy People 2020 products, but this analysis was the first time that we used all three measures and the first time that we had assessed kind of agreement between the three measures.  The second main take away is that for the objectives that we examined that did show detectable changes in disparities over time, there were more objectives that had a narrowing or decreasing and disparities than widening or increasing disparities over the decade. For all three measures. And this is an encouraging result.

And then the final take away is that we note that multiple measures may provide different approaches for assessing progress toward the elimination of health disparities, as there really is no gold standard for health disparities measurement.

HOST:  So why are these findings important?

DAVID HUANG:  These findings are important because, to our knowledge, they provide the first ever evaluation of national health disparities by race and ethnicity across all population based healthy people. 2020 objectives using the three measures of health disparities I mentioned earlier, and this provides for a more comprehensive assessment of progress towards achieving an overarching Healthy People 2020 goal to achieve HealthEquity, eliminate disparities and improve the health of all groups.

HOST: So why is it so difficult to measure disparities?

DAVID HUANG: Well, measurement of disparities among populations is complex and multidimensional, and each decision directly affects the analysis and findings. And these are decisions regarding methodological choices specifically. So one example in measuring disparities is that the researcher or analyst must choose a point of reference that all population subgroups were given characteristic, say, educational attainment or race and ethnicity are compared to when measuring disparities. In Healthy People, the reference point for the past two decades, Healthy People 2010 and 2020 has been the rate for the population subgroup with the most favorable rate. Previously, in Healthy People 2000, the overall population rate was used. This choice of the reference rate determines the size and the direction of the disparity, so it’s an important choice. Another choice that UM researchers need to make is whether to look at disparities in terms of absolute or relative terms. This is also another decision that affects the size of the disparity and even the direction of the change in disparities over time. And when looking at disparities on an absolute scale, we usually take the simple difference between two rates. While relative disparities are those calculated on a relative scale, by taking a ratio or a percent difference, for example, and while absolute measures may be easier to visualize and describe, relative measures are unit free, so they do lend themselves more naturally to comparisons across different types of measures. So I know there was a lot there, but really the kind of take away here is that no single measure is considered the gold standard in the measurement of health disparities, and it is useful to evaluate and compare multiple measures when time and resources allow, particularly because, as I mentioned, different measures can yield different conclusions, and to that end, starting in healthy people 2020 we have used a suite of measures to provide a fuller context of health disparities.

HOST:  How have methods to measure disparities evolved in Healthy People?

DAVID HUANG: That’s a question that would really take quite a bit of time to completely unpack, but I’ll just summarize some of the major changes briefly. First, there has been an evolution in expanding the scope of disparities, measures, which is aligned with an idea supported in the literature that measurement of disparities is complex. And again, a single measure is not sufficient to provide a full context of disparities. It is useful to evaluate and compare multiple measures, and we recommend that at a minimum, researchers or analysts look at both absolute and relative measures to provide a fuller context. In Healthy People, we have also evolved our thinking regarding the reference group. As I also mentioned earlier from the total population in Healthy People 2000 to the group with the most favorable raid starting in Healthy People 2010 and continuing into 2020. As I mentioned earlier.
For more in depth coverage on this topic, I actually encourage our listeners to check out and NCHS webinar titled The Evolution of Health Disparities Assessment and the Healthy People Initiative. This is actually scheduled for November 14th, and we’ll be posted to the NHS website for future reference.

HOST:  Over the years, going back to the beginning of the Healthy People initiative, do the data show we’ve made progress in narrowing disparities in health?

DAVID HUANG: So yes, we’ve taken a look at how we’ve done in terms of reducing and eliminating health disparities over the past couple of decades and for the most part, we have actually seen that there really hasn’t been a lot of change in disparities. Umm again, as this report did show, in some cases there were some narrowings. In some cases there were some widenings, but for the most part you know the most. The great majority of objectives have actually shown no change in either narrowing or widening of disparities, and this really highlights the fact that it’s important to continue to track disparities so that we can have the data that are needed to move the needle, certainly towards this goal of reducing and ideally eliminating health disparities.

HOST:  Would some of this lack of progress be too be due to the fact that all groups are making improvements, and therefore there’s no closing of the gaps in these disparities?

DAVID HUANG: So in Healthy People, we do have goals for all of the objectives and they’re sometimes to reduce something like a death rate or an illness. And sometimes the goal is to increase something like health insurance. And while we haven’t done a specific analysis to kind of look at how the objective is doing relative to kind of how the groups are doing in terms of eliminating the disparities, overall, we have kind of seen this pattern that they’re there hasn’t really been a reduction. So I think kind of to answer your question there, there may be some situations where overall the groups are all improving and the disparities are continuing. But there are also situations where overall the objective is actually not moving in the right direction and the disparities continue to persist or or really not change over time. So it, there really is, there really are two kind of separate analysis to be looking at here. One is kind of progress in terms of going in the right direction with the overall disparity. And then the other is to be looking at the disparities over time since there isn’t necessarily a direct correlation between those two analyses.

HOST:  Now, how will Healthy People, 2030 and other analyses build on this report?

DAVID HUANG: So for Healthy People, 2030, we’re really looking to expand on both the number and the types of disparities measures examined, which will help provide an even more complete picture of disparities. Next, we also understand that there are varying user needs related to health disparities, so we are aiming to provide a variety of graphics and text products related to disparities so that everyone from those looking for a quick bullet or take away to summarize disparities to those looking for a full complement of measures and technical content, we’ll be able to find what they need on our website. And finally, we are looking to provide a more user-friendly visualization related to health disparities on the website and for these visualizations to be provided for each disparity measure in our expanded set for the decade. We believe that these improvements taken aggregately will help users better understand and communicate health disparities to others.

HOST:  OK. Any other points you like to make?

DAVID HUANG: Well, I think just to be on the lookout for some of the additional content and features that I mentioned, we’re also gonna be releasing a NHS theories to report that looks at updated methods for measuring both progress and disparities for the current decade. Healthy people, 2030, we’re hoping to publish that sometime in the year 2023. So that’s another piece to be looking forward to. In addition to the disparities tool that I mentioned.

HOST:  OK. Well, thanks for joining us again, David.


HOST:  The month of November has featured several important data releases by NCHS.  The month began with a trio of releases on health insurance coverage, using data from the National Health Interview Survey.  Two reports, on geographic variation and on demographic variation were released on November 3, showing nearly 25 million working-age adults between ages 18 to 64 in the United States were without health insurance in 2021.  Texas, Georgia, and North Carolina had the highest rates of uninsured among this age group.

On the same day, new quarterly estimates on health insurance were released, covering the period through the second quarter of this year.  8.6% of all Americans did not have health insurance during April to June of 2022, a higher estimate than the 8.0% in the first quarter of the year.

There were other new data from the NHIS released the same day.  Interactive web dashboards were updated with new quarterly and biannual data on topics such as asthma, hypertension, mental health, disability, access to health care, and smoking – including e-cigarette use.

On November 4, a new report on alcohol-induced death rates was released, which generated a lot of interest for some its findings.  There was a 26 percent increase in alcohol-related mortality in one year from 2019 to 2020, triggering a great deal of interest in the role the pandemic may have played in this sharp increase in alcohol deaths.

On November 15, NCHS updated another quarterly dashboard, this one on infant mortality, through the first quarter of this year.  The national infant mortality rate remained steady at 5.4 infant deaths per 1,000 live births.

The following day, NCHS put out two mortality reports featuring 2020 final data.  The first report looked at mechanisms of suicide by race and Hispanic origin over the past two decades.  The second report examined leading causes of death by race and ethnicity over the past two decades among people in their “prime years” of life – 25 to 44 years.

On November 17, another vital statistics report was released, on home births in the United States.  The report found that during the pandemic, there was a surge in home births in the U.S. – a 34% increase from 2019 to 2021.

On November 22, NCHS released a report on emergency department visits during 2020, based on data from the National Hospital Ambulatory Medical Care Survey.  The report showed that emergency room visit rates were lowest for those with private health insurance and highest for those with Medicaid, suggesting that the ER continues to be used for primary care in some communities.  Nearly 7% of all ER visits had a mention of COVID-19 in some capacity.

On November 29, NCHS released a new analysis from the National Health and Nutrition Examination Survey – or NHANES – on people’s awareness of the U.S. Department of Agriculture’s “My Plate” plan.  This plan is related to the government’s recommended dietary guidelines for Americans.  The data show less than 1 in 3 Americans have heard of “My Plate” and less than 1 in 10 are actively trying to follow its recommendations.

Finally, the month closes out today with three new mortality reports focusing on the 65-and-over population:  one report examines deaths by unintentional falls, another documents drug overdose deaths, and the third report looks at alcohol-induced deaths.

Death rates from unintentional falls are more than twice as high for 65-74 year-olds as for 55-64 year-olds; death rates for 75-84 year-olds are nearly four times as high as for 65-74 year-olds, and death rates for people 85 and over are over four times as high as for 75-84 year-olds.

The death rate from drug overdoses among 65-74 year-olds is nearly as high as that for 15-24 year-olds and the death rate from alcohol-induced causes in that age group is the third highest of any age group.

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Page last reviewed: November 29, 2022
Page last updated: November 29, 2022