PODCAST: COVID-19 Mortality by Occupation and Industry

October 28, 2022


HOST:  We talked this week with Ari Minino, a statistician with the NCHS Division of Vital Statistics and co-author on a new report out on October 28th on COVID-19 mortality in 2020 by occupation and industry.  The report was a collaborative analysis conducted by NCHS and NIOSH – the National Institute for Occupational Safety and Health.

HOST:  Before we get into what your study is all about, can you briefly tell people or caution people what your study does not cover.

ARI MININO:  The study is limited to information on what the usual occupation and industry of the decedent was.  That is, what was the work or usual job that the person did for most of his working life.  So this is not, for example, a study on exactly where it was that the person contracted the condition – in this case COVID-19.  It is a study trying to associate the co-determinant of work which is co-determinant of health and how that relates to the, in this case the risk of the person died from COVID-19. That is a delicate distinction, but I think it’s important one.

HOST:  So, in this study your coauthors actually were from the National Institute for Occupational Safety and Health, is that correct?

ARI MININO:  That’s correct.  Yeah, it’s important to note that this is a close collaboration between the National Institute for Occupational Safety and Health and the National Center for Health Statistics and this goes back many decades ago.  We used to have data on the usual occupation and at the industry of the decedent included as part of our mortality data for the years 1984 through 1998.  And it was only recently – and probably I’m going to say it started in 2018 – there was a signed agreement between the two agencies that we started working towards trying to incorporate these data again into the mortality data.  And so the first year that we’re including this data is for 2020 and we’re very excited, very happy that these data are finally part of the mortality, national vital statistics file, and this report that we’re discussing is kind of like our introduction to that.  And my colleagues, Dr. Andrea Steege and Dr. Rachael Billock, they were the true driving force for this study, and they produced most of the coding and they did actually all of the analysis, all the analytical work.  And they were with us in NCHS on a detail for the duration of the period of this study, when this study was conducted.

HOST:  It’s obviously very difficult or almost impossible to determine where and how anyone gets COVID, and so that’s one of the limitations you wanted to point out, out front, correct?

ARI MININO:  That is correct.  One other important limitation of this work is that this is not a complete global or universal variable in the sense that it does not cover all of the decedents but has some specific limitations.  We only included data for 46 States and New York City, which is a separate registration area, and we only include information for decedents age 10 years and up to 64.

HOST:  And just for those who aren’t familiar with the terminology, when you say “decedent” you’re talking about the people who died, in this case from COVID-19.

ARI MININO:   That is correct.  This information is entirely based on information collected from the death certificate of all the diseases or in this case the decedents who died from COVID-19.

HOST:  Now, turning to what your study did uncover, your study found some interesting things about mortality from COVID-19 and occupation.  And what was in your view the biggest finding in your new report?

ARI MININO:   Well, the biggest finding is something that was sort of expected which is that when we discuss risk, the specific occupation that the decedent had or the usual occupation of this varied quite substantially in terms of the risk of dying from COVID.  For example, when we look at the death rate, which is only one of the measures that we looked at, we found that workers in protective service occupations were the ones who had the highest death rate from COVID.

HOST:  And when you say “protective services” give us some examples.

ARI MININO:  These are policemen, these are people working building security, that type of occupation.  So the other group that had very high death rates were people who worked in accommodation and food service industries.  These are people who work in, for example, hotels.  These are people who work in restaurants. 

HOST:  OK so these are the occupational settings where you mentioned you would expect to see sort of higher mortality.  Were there any surprises in looking at COVID mortality across different occupational settings?

ARI MININO:  There were some surprises.  In particular, when we looked at the measure that we called the “proportionate mortality ratio.” And this is not an indication necessarily of risk, but rather of a disproportionate amount of or a disproportionate count of people who died from COVID-19 relative to all the other decedents.  This is not a measure that can exactly relate to risk necessarily.  This particular way of looking at decedents, we found some variation when we look at deaths by race and Hispanic origin.  In particular, in the way in the specific occupations that showed higher proportions of COVID-19 mortality.

HOST: I guess what you’re saying is that there were demographic groups with higher COVID mortality and some interesting comparisons along occupational lines, is that correct?

ARI MININO:  Yeah and something that is important is that we used two measures.  The main measure that we use, the statistical measure, is the “proportionate mortality ratio.”  And we use that to analyze the differences.  In particular, among the different race and Hispanic origin groups.  That’s because we didn’t have a good sample size with the denominator data.  And it’s very difficult to get denominator data for these occupation and industry groups because the Census is not geared exactly to look at that, and to produce good estimates for that.  And so we looked at PMRs, and that is something – it’s very important to distinguish that, for example when you look at a high PMR, it does not necessarily mean that there is a higher risk for the condition, just because we found a high PMR for a particular occupation.  It just means that there’s a disproportionate number of COVID-19 deaths among the decedents, and its just the numerator. 

HOST:  Doesn’t that sort of speak to the broader issue – that we’re not really assessing risk with this study, right?

ARI MININO:  Yeah, with the measures that are done using the death rate, yes they do speak to risk because we do use a denominator that was available from census that would fit the numerators but–

HOST:  The other measures, that’s a different story.

ARI MININO:  It’s a different story, yeah.  You see that the results when we look at PMRs and in particular when we look at PMRs by race and Hispanic origin, we find that when we look at the non-Hispanic American Indian and Alaska Native population, for example, as well as for non-Hispanic white, we find that the highest PMRs were for people with occupations in community and social services types of occupations.  However, when we look at non-Hispanic Asian and non-Hispanic Black, decedents were observed among those in protective service occupations – same as we found for the overall population.

HOST:  And again, that is using the “proportionate mortality ratio.”

ARI MININO:  Uh-huh.

HOST:  And you indicated that that isn’t necessarily a measure that defines risk but rather—

ARI MININO:  A disproportionate number of COVID-19 deaths among that particular group when compared with the rest of all of the decedents in that particular group for all other occupations.

HOST:  So we would close then by asking if there’s anything else you’d like to mention about your study?

ARI MININO:   I think this is a good introductory study for bringing in awareness about how we have these data for 2020.  Because these data, even though we had industry and occupation data for a selected number of states between 1984 and 1998, this is the first time that we’ve included these data in the mortality file.  And I think – well, because of course of the pandemic situation – I think I thought that it was a very good idea to do an introductory study focusing on COVID.  But this is only the first of a series of studies that we have planned.  And we’re gonna be looking at drug overdose and industry and occupation on how those how those two relate in terms of mortality.

HOST:  Well thanks very much for joining us Ari.


HOST: October was a busy month for NCHS, starting with the release of the latest quarterly provisional birth data in the United States on October 11th.  The quarterly dashboard features data on a number of measures, including the fertility rate in the United States.  The general fertility rate is the number of births per 1,000 females ages 15-44, and the rate increased from 55.2 to 56.4 in the one-year ending in Quarter 2 of 2022 compared with the previous year. 

The next day, on October 12th, NCHS released the latest summary health statistics for children and adults in the United States, based on data from the National Health Interview Survey or NHIS.  This dashboard features a wealth of data on a variety of measures, including smoking.  The NHIS data shows the percentage of adults in the U.S. who smoke cigarettes has declined from 14% in 2019 to 11.5% in 2021. 

The same day, NCHS released the latest provisional monthly estimates of drug overdose deaths in the nation.  108,022 Americans died from overdoses in the one-year period ending in May of 2022.

The following day, on October 13, NCHS released a new report on telemedicine use for 2021.  The study, featuring data from the NHIS, showed that 4 in 10 adults in the United States used telemedicine in the past year. 

That busy week closed out on October 14 with a new study on COVID-19 mortality among older Americans age 65 and up.  The study showed that during the first year of the pandemic, the death rate from COVID for people age 85 and up was nearly three times higher than the rate for people ages 75-84, and seven times higher than the rate for people ages 65-74.

The following week, on October 19, NCHS released a new report on fetal deaths in the United States from 2018 to 2020.  The study showed that there were nearly 47,000 fetal deaths at 20 weeks of pregnancy or longer during this period.

NCHS rounded out the month with three new data releases in the last week, starting with an October 25 study on COVID-19 mortality during the first year of the pandemic by urban-rural status, showing as expected that people living in the most urban areas of the country had higher mortality from COVID than in other geographic areas.

And on October 26, NCHS updated another of its quarterly dashboards, this one on leading causes of death in the country, through the one year period ending in Quarter 1 of 2022.  The data show a drop in the country’s death rate during this period compared to the year before.

PODCAST: The Toll of COVID-19 on Physician Practices

September 30, 2022


HOST:  The COVID-19 pandemic took a major toll on the U.S. health care system.  In a new report released on September 28, data from the National Ambulatory Medical Care Survey were used to examine how COVID-19 impacted physician practices around the country.

Joining us to discuss that new study is Zach Peters, a health statistician with the NCHS Division of Health Care Statistics.

HOST:  What did you hope to achieve with this study?

ZACK PETERS:  This study was intended to produce nationally representative estimates of experiences at physician offices.  So it’s a physician level study and we really wanted to highlight some of the important experiences physicians had due to the pandemic, such as shortages of personal protective equipment.  And it highlights whether testing was common in physician, whether physicians were testing positive or people in their office were testing positive for COVID-19 given that they were on the front lines of helping to treat patients.  So we really wanted to touch on a broad set of experiences faced by physicians.  This certainly isn’t the first study to assess experiences and challenges faced by health care providers during the pandemic but often times those other studies are limited to specific facilities or locations or cohorts and can’t be generalized more broadly.  So a big benefit of a lot of the NCHS surveys is that we can produce nationally representative estimates and this study is an example of that.

HOST:  And what kind of impact has the pandemic had on physicians and their practices?

ZACH PETERS:  In having done quite a bit of literature review for this project it became pretty clear – and I think just listening to the news you sort of understood a lot of the impact.  A lot of research has shown that that health care providers experienced a lot of burnout or fatigue.  There was a lot of exposure and what not to COVID-19.  Long hours… So there’s a lot out there in in the literature that sort of cites some of the challenges.  What we really, what this study highlighted was it was the level of shortages of personal protective equipment that were faced.  About one in three physicians said that they had they had experienced personal protective equipment shortages due specifically to the pandemic .  The study highlighted that a large portion of physicians had to turn away patients who were either COVID confirmed or suspected COVID-19 patients.  And I think the last thing this really helped to show was the shift in the use of telemedicine due to the pandemic.  So prior to March of 2020 there were less than half of physicians at physician offices who were using telemedicine for patient care and that number, that percentage jumped to nearly 90% of office based physicians using telemedicine after March of 2020.  So this is sort of adding to the broader literature with some nationally representative estimates of experiences that providers had due to and during the pandemic.

HOST:  So what sort of personal protective equipment was most affected during this study?

ZACH PETERS:  It’s a good question.  The way in which we asked the questions about shortages of “PPE” – I’ll call it I guess – don’t allow us from really untangling that question.  We asked about face mask shortages, N-95 respirator shortages specifically, but then the second question we asked sort of grouped isolation gowns, gloves, and eye protection into one question.  So physicians didn’t really have the chance to check off specifically what they had shortages of other than face masks.  So it’s somewhat hard to untangle that but these results show that about one in five physicians faced N-95 respirator, face mask shortages due to the pandemic and a slightly higher – though we didn’t test significance in this in this report – a slightly higher percentage, about 25% of physicians, had shortages of isolation gowns,  gloves, or eye protection or some combination of those three. 

HOST:  And you say that nearly four in 10 physicians had to turn away COVID patients.  Now, was this due to a high volume of patients or a lack of staff?

ZACH PETERS:  Again that’s another great question. I think unfortunately we weren’t able to ask a lot of these really interesting follow-ups to some of these experiences. We didn’t get to pry physicians on some of the reasons why they had these experiences, including why they had to turn away patients.  So unfortunately we’re not able to answer some of the “why” questions that we would like with these data.

HOST:  And do you have any data on where these patients were referred to, the ones that were turned away?  Do you have any information on that?

ZACH PETERS:  Again unfortunately this specific question wasn’t something that we asked in the set of new COVID questions introduced in the 2020 NAMCS we did ask a question about whether physicians who had to turn away patients had a location where they could refer COVID-19 patients.  So there are a few reasons – we haven’t assessed that measure in this work so far, but it’s certainly an area we can dig into more especially as we have additional data from the 2021 NAMCS and can try to combine over time.

HOST:  Does it look like the shift to telemedicine visits is here to stay?

ZACH PETERS:  The broader literature sort of highlights that these changes are broad and likely indicate that physician offices and different health care settings have built up the infrastructure to allow for telemedicine use in the future.  And so it’ll be interesting to see if, as waves of COVID or other infections ebb and flow, if we see that the use of telemedicine kind of ebbs and flows along with that.  But I think the option for telemedicine is something that health care settings won’t get rid of now that they have them. 

HOST:  Sticking with the topic of telemedicine – did physicians list any benefits to telemedicine visits other than limiting exposure to COVID-19?

ZACH PETERS:  The set of questions that we asked physicians were limited in scope and we didn’t really have that level of follow-up.  There are some additional questions about telemedicine use that we asked and hope to be able to dig into further.  We asked physicians what percentage of their visits they had used telemedicine and some other questions about just kind of the scope of use, but not necessarily the benefits that they felt they received due to using telemedicine.

HOST:  Is it possible that you might be getting some data on these questions in the future?

ZACH PETERS:  These questions were introduced part way through the 2020 survey year, so we were only able to ask half of our physician sample about these experiences in the 2020 survey.  But we kept the exact same set of COVID related questions in the 2021 NAMCS survey year and so we’re working to finalize the 2021 data and hope to be able to look into some of the more nuanced aspects of this that we might be interested in, such as trends over time if we combine years.  So we might be able to assess differences in experiences based on the characteristics of physicians.  So yeah, we asked these specific questions in the 2021 survey year so hope to have some additional information to put out for folks.

HOST:  You were talking a little bit about the fact that you made changes to the National Ambulatory Medical Care Survey, which this study is based on, which allowed you to collect more complete data during this period. Could you again sort of go over what sort of changes you made?

ZACH PETERS:  Yes the NAMCS team with the Division of Health Care Statistics, we made changes to a few of our surveys partway through the 2020 survey year.  Partly out of necessity and partly out of just interest in an unfolding public health crisis.  So for NAMCS two big changes were made. The first was that we had to cancel visit record abstraction at physician offices.  So historically we have collected a sample of visit records or encounter records from physicians to be able to publish estimates on health care utilization at physician offices due to sort of wanting to keep our participants safe, our data collectors safe, and patients safe.  We cancelled abstraction partly into the 2020 survey year so that was an important change in that we won’t be able to produce visit estimates from the survey year.  But the other change that we made – I think I alluded to it earlier – was that partway through the survey year we introduced a series of COVID-19 related questions, which is what this report summarizes.  And the reason it came partway through the survey year is simply due to the fact that adding a series of new questions to a national survey takes a lot of planning and a lot of levels of review and approval.  So this is partly why we were only able to ask these questions of half of our survey sample.

HOST:  Are there any other changes forthcoming in the NAMCS or for that matter any of your other health care surveys?

ZACH PETERS:  Historically there have been a few different types of providers that have been excluded from our sample frame.  We didn’t include anesthesiologists working in office-based settings, radiologists working in office-based settings.  So we had a few different types of promoting specialties that we couldn’t speak to in terms of their office characteristics and their care that they provided.  In future years we are hoping to expand to include other provider types that we haven’t in the past so I think that’s the big change going forward for the traditional NAMCS.  We also have a kind of a second half of NAMCS that looks at health centers in the U.S., and the big change for that survey in the 2021 survey years that we are in is instead of abstracting a sample of visit records, are we are starting to collect electronic health record data from health centers.  So that’s another a different portion of NAMCS but those are a couple of the big changes at high level that are implementing in NAMCS. 

HOST:  What would you say is the main take-home message you’d like people to know about this study?

ZACH PETERS:  I think the main strength of using data from NCHS in general is that many of our surveys allow for nationally representative estimates and NAMCS is the same in that regard.  We sampled physicians in a way that allows us to produce nationally representative estimates.  And so I think this study highlights how we’re able to leverage our surveys in a way that other studies that you might see in the literature can’t in that they’re more cohort-based.  So I think another important aspect of this is just that it highlights an example of some of the adaptations that DHCS end and NCHS more broadly, some of the adaptations that we made during the pandemic to better collect data and disseminate data.  And so outside of the topic being hopefully important to understand how physicians nationally experienced various things related to the pandemic, this highlights some of the ways in which NCHS was able to remain nimble during a public health crisis.


HOST:  On September 1, NCHS released a new report looking at emergency department visits for chronic conditions associated with severe COVID illness.  The data, collected through the National Hospital Ambulatory Medical Care Survey, were collected during the pre-pandemic period of 2017-2019 and serve as a useful baseline, since it is well established that chronic conditions increase the risk of hospitalization among COVID patients.  The report showed that during this pre-pandemic period, hypertension was present in one-third of all emergency department visits by adults, and diabetes and hypertension were also present together in one-third of these visits.

On the 7th of September, NCHS released a study focusing on mental health treatment among adults during both the pre-pandemic and pandemic period, 2019 to 2021.  It has been documented by the Household Pulse Survey and other studies that anxiety and depression increased during 2020 and the beginning of 2021, and this new study focuses on the use of counseling or therapy, and/or the use of medication for mental health during this period.   The study found there was a small increase in the use of mental health treatment among adults from 2019 to 2021, with slightly larger increases among non-Hispanic white and Asian people.

Also this month, NCHS updated two of its interactive web dashboards, featuring data from the revamped National Hospital Care Survey.  On September 12, the dashboard on COVID-19 data from selected hospitals in the United States was updated, and two days later the dashboard featuring data on hospital encounters associated with drug use was updated. 

On the same day, September 14, NCHS released the latest monthly estimates of deaths from drug overdoses in the country, through April of this year, showing 108,174 people died from overdoses in the one-year period ending in April.  This death total was a 7% increase from the year before.  Over two-thirds of these overdose deaths were from fentanyl or other synthetic opioids. 

On September 29, the latest infant mortality data for the U.S. was released, based on the 2020 linked birth and infant death file, which is based on birth and death certificates registered in all 50 states and DC. 

Finally, September is Suicide Prevention Month, and on the final day of the month, NCHS released its first full-year 2021 data on suicides in the country.  For the first time in three years, suicide in the United States increased.  A total of 47,646 suicides took place in 2021, according to the provisional data used in the report.  The rate of suicide was 14 suicides per 100,000 people.


PODCAST: Life Expectancy Fell in 2021 for the Second Year in a Row

August 31, 2022


HOST: In 2020, the United States experienced the biggest one-year drop in life expectancy since World War II, mostly due to the pandemic.  All 50 states had declines in life expectancy that year.  These declines were detailed in a new report released in mid-August.  On the last day of the month, NCHS released new estimates for 2021, showing life expectancy dropped nearly one more year for the country from the 2020 level.

There were some significant differences between the declines that took place in 2020 and those which occurred in 2021, particularly among different race/ethnic groups.

We talked to NCHS Mortality Statistics Chief Robert Anderson about this and other matters related to the two new studies on life expectancy.

HOST:  So there are two new reports out this month on life expectancy – the first was a report on 2020 life expectancy by state.  First of all, how did the arrival of the pandemic impact life expectancy on the country as a whole in 2020?

ROBERT ANDERSON:  Well by the time we got to the end of 2020, life expectancy had dropped almost two years, it was like 1.8 years, and COVID was, you know, largely responsible for that decline.

HOST:  So what were some of the striking declines in life expectancy from 2019 to 2020 at the state level.

ROBERT ANDERSON:  Certainly there was some state variation in the change in life expectancy, but you know overall we saw declines for every state from 2019 to 2020.  Overall the change was I said almost two years, 1.8 years, a 1.8 year decline from 2019 to 2020 overall, but then if you look at the declines by state of course they vary from about a three-year decline to about a two-year decline. So it’s quite a bit of variation in the decline in life expectancy, although we did see declines for all states.

HOST:  So presumably, the states with the largest declines in life expectancy during 2020 were also the states that have the highest mortality from COVID?

ROBERT ANDERSON:  That’s essentially correct.  I mean it’s a little more complicated than that because there’s some other things going on.  We saw increases for some other causes of death and of course increases in drug overdose deaths also had an impact, but overall COVID-19 was the primary factor.

HOST:  And so I guess the converse would be true as well – states with the smallest declines in life expectancy in 2020 were those states that had lowest mortality from COVID – would that be correct?

ROBERT ANDERSON:  Yeah that’s essentially correct.

HOST:  Now are there any other interesting findings in the state life expectancy report?

ROBERT ANDERSON:  Yeah you know the declines, if you look at things on a regional basis you see larger declines in the South, Southwest and in the Northeast. Well, New York, New Jersey in particular.  And then you know a much smaller declines in the upper Northeast – you know, Maine, New Hampshire, Vermont.  And in the Northwest – Washington, Oregon, Idaho, that area.  And of course that corresponds as we said with the level of COVID mortality in those states during 2020.

HOST:  So turning to the 2021 national report – did the decline in life expectancy continue in year two of the pandemic?

ROBERT ANDERSON:  It did… We saw an additional decline of nearly a year – 0.9 years overall – so yeah, we saw an additional decline in life expectancy.

HOST:  And so I guess this lines up with the fact that there were more COVID-19 deaths in 2021 than in 2020 right?

ROBERT ANDERSON:  That’s right, yeah that’s what we expected – because of the higher mortality in 2021 compared with 2020, we expected an additional decline in life expectancy.  And in fact that’s what we’re seeing.

HOST:  And what about the disparity between the sexes and life expectancy?  It’s always existed but it appears the pandemic has widened that gap.

ROBERT ANDERSON:   Yeah that’s right.  Typically, men have lower life expectancy than women and that’s because men have higher mortality than women overall.  And we do know that men were disproportionately affected by the pandemic – COVID-19 death rates were higher for men than for women – and so it’s not surprising that we would see a slightly larger disparity between males and females during the pandemic.

HOST:   So what race ethnic groups saw the biggest decline in life expectancy during 2021?

ROBERT ANDERSON:   From 2020 to 2021, the American Indian population really was most affected – there was a 1.9 year decline in life expectancy.  That’s followed by the non-Hispanic white population by about a year.  Then non-Hispanic black population about 7/10 of a year… and then the Hispanic population and the Asian population – the declines were much smaller during 2021. A 0.2 year decline for the Hispanic population, about a 0.1 year decline for the Asian population.

HOST:  Now over the span of the entire pandemic, what has been the cumulative impact on life expectancy among those race ethnic groups?

ROBERT ANDERSON:  Yeah I think that’s an important question.  Overall, the decline in life expectancy is about 2.7 years, a nearly three-year decline which is quite substantial.  And then quite a lot of variability by race and ethnicity.  For the American Indian population, the decline was 6.6 years from 2019 to 2021.  That’s just astounding.  For the Hispanic population it was a 4.2 year decline; for the black population about a four-year decline; for the white population, 2.4 years and for the Asian population 2.1 years.

HOST:  So it sounds like for the Hispanic population there is a lot more of an improvement I guess in 2021 is that correct?

ROBERT ANDERSON:  I’m not really sure I would say it was an improvement. The decline wasn’t as large in 2021 as it was in 2020, that’s true, but it did not improve – it continued to drop, just didn’t drop by as much.

HOST:  So besides COVID, were there any other leading causes of death that contributed to this decline in life expectancy?

ROBERT ANDERSON:  Yes – the main one is unintentional injuries, and this is mostly drug overdoses.  You know, there’s some other causes that’re grouped with unintentional injuries, includes motor vehicle accidents and falls and things like that.  But what really stands out in terms of sort of increasing mortality and which is responsible for the decline in life expectancy would be the drug overdose deaths so it’s second to COVID-19 in terms of its impac.

HOST:  And a lot of people would say that that increase in overdose deaths may or may not be indirectly tied to the pandemic stress right?

ROBERT ANDERSON:  Yeah it’s hard to say for sure exactly how it’s related or whether individual cases are related, but you know we were seeing sort of a flattening and even slightly declining drug overdose death rates just prior to the pandemic and of course a quite steep increase in drug overdose mortality during the pandemic.  So it’s hard to tie it directly because we started to see increases late in 2019 before the pandemic became, before it emerged, but then once it did, once the pandemic did emerge, then the increase in drug overdose mortality really went up quite steeply.

HOST: Any other points of either of these reports you like to make?

ROBERT ANDERSON:  Well I’ll just mention with the 2021 report, that the data are provisional still.  The data for 2021 probably won’t be final until December, that’s our target date for release of the 2021 final data.  So there could be some slight differences once we finalize the data, but at the point at which we cut the data to produce this report we had more than 99% of deaths so I don’t expect any substantial differences between this provisional report and what we will have based on our final data.

HOST:  Dr. Anderson thank you for joining us.

ROBERT ANDERSON: Thank you very much.


HOST:  Overall, August was an extremely busy month at NCHS.  The month started off with a new report on physical therapy, speech therapy, and rehabilitative and occupational therapy among veterans compared with non-veterans, using data from the National Health Interview Survey.  The study showed that veterans are more than 50% likelier than non-veterans to have had any of these therapies.  The same week, NCHS released its latest annual report on fetal mortality in the United States for 2020.  A total of 20,854 fetal deaths at 20 weeks of pregnancy or longer were reported in 2020.

Another study, using NHIS data, looked at organized sports participation among U.S. children ages 6-17.  The study showed that over half of kids in this age group participate in organized sports.

On August 18th, NCHS released the latest monthly data on drug overdose deaths in the country, documenting that over 109,000 overdose deaths occurred in the United States during the one-year period ending in March 2022.

The official public use file for births in the United States for 2021 was released on August 29, accompanied by a Data Brief summarizing the key findings from these final data.  On the same day, the quarterly provisional release of infant mortality data was released in an interactive data visualization for the web, featuring full-year 2020 numbers. The post neonatal mortality rate in the U.S. increased in 2020 from the same point in 2019.  The post neonatal mortality rate is the number of deaths among infants between 28 and 364 days of age per 1,000 live births.

And last, a new report using data from the 2020 National Health Interview Survey shows that about one-quarter of adults in the United States age 18 and over have met the national physical activity guidelines for both aerobic and muscle-strengthening activities.

PODCAST: Sleep Difficulties & Patterns Among Americans

June 30, 2022


HOST: The American Academy of Sleep Medicine recommends between 9 and 12 hours of sleep for children between ages 6 and 12, and 8 to 10 hours of sleep for teens ages 13 to 18.  However, only two-thirds of school-age children meet these recommendations.

At the same time, the American Academy of Sleep Medicine and the Sleep Research Society recommend that adults receive at least 7 hours of sleep per night, and yet, more than a quarter of adults do not meet this recommendation. Signs of good sleep quality include taking less time to fall asleep and not waking up often or for long periods of time.

Last week, NCHS released two new reports on sleep habits among children and adults, using data from the 2020 National Health Interview Survey – or NHIS.

Today, we’re joined by the lead author of the report on adults, Dzifa Adjaye-Gbewonyo, who is also a co-author on the report on children’s bedtime habits.

HOST:  OK Dzifa, thank you for joining us.  Could you talk a little bit about why your team conducted these analyeis on sleep and sleep behaviors?

DAG:  Sure.  So the 2020 National Health interview survey or NHIS was the first time that data on sleep had been collected on adults since the survey was redesigned in 2019, and we wanted to be able to provide updated information on adult sleep.  The sleep questions had also changed slightly from earlier versions of the NHIS and the 2020 survey was also the first time that sleep data had ever been collected on children in the NHIS.  So we wanted to be able to analyze the adult and child sleep content and produce estimates for some of these measures.

HOST:  So – second question – just stepping back… In a general sense, why is sleep an important part of a healthy lifestyle?

DAG:  So sleep is vital for health and well-being.  Inadequate sleep and issues with falling or staying asleep have been associated with poor health outcomes such as high blood pressure, heart disease, diabetes, obesity and even mortality.  Insufficient sleep also affects children’s physical and mental health, and increases the likelihood of cognitive and behavioral issues, Type II diabetes, obesity and injuries.

HOST: OK and what is the recommended amount of sleep for an adult?

DAG:  So for adults this suggested amount of sleep is at least seven hours a night based on recommendations from the American Academy of Sleep Medicine and the Sleep Research Society.

HOST: OK and what about the what is recommended for children?

DAG:  For children, the American Academy of Pediatrics recommends between 10 to 16 hours of sleep for children under five years, 9 to 12 hours for children 6 to 12 years, and eight to 10 hours for adolescents aged 13 to 18.

HOST:  In your study on adults how did you define sleep difficulties?

DAB: We defined, we looked at two measures for sleep difficulties which we called “trouble falling asleep” and “trouble staying asleep” and those were based on survey questions in the questionnaire so the question on trouble falling asleep was based on a response of if adults answered “most days” or “every day” to the question “During the past 30 days how often did you have trouble falling asleep?” and similarly for” trouble staying asleep” it was also based on a response of “most days” or “every day” to the question “During the past 30 days how often did you have trouble staying asleep?”

HOST: OK now getting into your studies, what were the key findings in your study on adults?

DAB: We found that one in seven adults in the US had trouble falling asleep and about 18% of adults had trouble staying asleep.  These sleep difficulties were more common in women than men, and older adults aged 65 and over had less trouble falling asleep while younger adults aged 18 to 44 had less trouble staying asleep.  Problems falling and staying asleep decreased as family income increased and as place of residence became more urban.  Sleep difficulties also varied by race and ethnicity stand by education level.

HOST: Now your study used 2020 data – was there any insight about how the pandemic impacted sleep patterns?

DAG:  We looked at 2020 data as a whole, so analysis on changes in sleep patterns during the pandemic were beyond the scope of this report.  There is more specific information about when the data were collected, but it might be difficult to tease out the reasons for any changes observed across time periods.  Especially because the data collection process also changed during the pandemic. Prior to 2020 data on sleep were last collected in the 2018 NHIS.  However, they may not be directly comparable to 2020 data due to changes in the survey questions.

HOST:  Would it be accurate to say that your findings here suggest that economic or money concerns have an impact on people sleep habits?

DAG:  Well we can say that there is a link between economic factors and sleep difficulties and that complaints of trouble falling and staying asleep and adults are lower with increasing family income, but we cannot say with certainty what the direction of this impact is from these data alone.  For example, a family’s economic situation may affect someone’s ability to fall or stay asleep, and sleep difficulties could also have some effects on economic status.  So since the survey is a snapshot in time either or both impacts may be possible.

HOST:  Right and anecdotally that would certainly make sense.  So your other study in which you were a co-author on looked at children’s bedtime habits.  How important is it bedtime routine for kids?

DAG:  Studies show that children who have regular bedtimes are more likely to get the amount of sleep they need.  And sleep routines are also linked to other outcomes in children.  For instance, better cognitive performance and a lower risk of obesity.  So bedtime routines are quite important for children.

HOST:  So does your study show that kids are getting the recommended amount of sleep then?

DAG:  Well our data did not look specifically at the amount of sleep children are receiving, but based on other sources just under 2/3 of children get the recommended amount of sleep.  So about 1/3 of children in the U.S. do not get enough sleep.

HOST:  And how does your study define a regular bedtime for kids?

DAG:  For a regular bedtime for children, we define that based on responses to the question “In a typical school week, how often does the child go to bed at the same time?” and so the response options were “Never,” “Some days,” “Most days,” or “Every day,” and we use “Most days” or “Every day” to define having a regular bedtime.

HOST:  What does that study tell us about family structure and bedtime habits and children?

DAG:  Well our results showed that there does seem to be a difference in regular bedtime habits depending on children’s family structure.  Children living in single parent families were less likely to have a regular bedtime every day or most days compared with children living in two-parent families.

HOST:  And which children are more likely not to have a structured bedtime routine?

DAG:  Older children aged 12 to 17 are more likely to not have a regular bedtime, as well as Hispanic and non-Hispanic black children, children living in families with lower incomes, and children to live in communities that are more socially vulnerable.

HOST:  One would assume, too, if they have parents who work evenings or something, or a parent travels a lot, that that would have an impact on bedtime routine?

DAG:  Yeah that’s possible – we didn’t get to look specifically at work schedules and travel but that would be something to look into to tease out some of those impacts.

HOST:  OK so do you have any other take home messages about either report you’d like to emphasize?

DAG:  Well, I think one thing that we would like to emphasize we hope is that these reports will improve our understanding of sleep difficulties in adults and of children’s bedtime routines.  So we hope that they can be useful sources of information that can help inform future research and also inform sleep interventions and targeting sleep interventions for subgroups that may be more at risk.


HOST: NCHS is part of a team of federal agencies, led by the Census Bureau, that collaborate on the Household Pulse Survey, which has produced mental health and health care access data, along with several other topics, during the pandemic.  On June 22, the Pulse Survey for the first time included data on “long COVID,” defined as “symptoms lasting three or more months after first contracting the virus, and that they didn’t have prior to their COVID-19 infection.”  The first round of data, collected from June 1st to June 13 showed that nearly 1 in 5 Americans who have had COVID-19 still have long COVID.

NCHS released two other new reports this month as well.  On June 23, data from the National Ambulatory Medical Care Survey was examined in a new report on Health Centers in the United States.  The report found that a third of the visits to these health centers were for preventive care.  Another third of visits were due to chronic problems and the other third were due to new problems.  6 in 10 health care center visits involved screening, exams, and health education or counseling.  4 in 10 visits involved lab tests of some kind.  Most of these visits to health care centers were paid for by Medicaid.

And finally, this month NCHS released a report on maternal health characteristics and infant outcomes to women born both in and outside the United States. The report reveals that over 1 in 5 women who gave birth in the United States were born outside the U.S.  Over half of these women born outside the U.S. were from Latin America, who accounted for 12% of all women giving birth in 2020.  Over a quarter of women born outside the U.S. were born in Asia, and accounted for 6% of all births.

PODCAST: NHANES Pre-Pandemic Data Release, Part II

May 27, 2022


(Based on the June 16, 2021, webinar, National Health and Nutrition Examination Survey 2017–March 2020 Pre-pandemic Data Release )

HOST:  On this edition of Statcast, we continue with the second part of the NHANES webinar, which focuses on the plans for the prepandemic and partial year 2020 data, with an overview of a published report from 2021 on health estimates from this data set, from Dr. Bryan Stierman

STIERMAN:  The health outcomes selected for estimates include for children, obesity and dental caries; for adults, hypertension, obesity, severe obesity, and diabetes; and for older adults, complete tooth loss. These health outcomes were selected for estimates because they were able to be calculated from the files currently released publicly available on the NHANES website.

Today we present estimates by several covariates including sex, age groups, race and Hispanic origin, and family income. Other covariates and stratification by sex are included in the accompanying National Health Statistics Report publication.

As is usual with NHANES analyses, to calculate these estimates we accounted for the complex, multistage probability design of NHANES, including the unequal probability of selection.

Provided sample weights were used for calculations. For estimates for diabetes, fasting sample weights were used. For all other estimates, examination simple weights for used. Standard errors were estimated using Taylor series linearization. And adult estimates were directly age-adjusted to the 2000 projected U.S. census population.

As would be expected, the overall estimates for each health outcome calculated for 2017 through March 2020 are similar to those from 2017 through 2018 alone. This reflects both the methodological adjustments, as well as the patterns in the prevalence estimates, which typically are not expected to vary by large amounts from when one year to the next in NHANES due to the relatively small sample size and a one-year data collection.

The data from 2017 through March 2020 provide an increase in sample size, generally about 1.5 to 2 times the sample size of that from 2017 through 2018 alone. As expected, this increase in sample size generally leads to smaller standard errors, as can be seen with all health outcomes here except for complete tooth loss. However, for some estimates in some demographic subgroups, increased variation in the sampling weights, increased variation in the true underlying population values of the health outcomes from the data added from 2019 through March 2020, or both may result in equivalent or increased variance of estimates, as seen here with complete tooth loss, which has equivalent standard errors from both time periods.

We found that 19.7% of children aged 2 through 19 years had obesity, defined as a body mass index greater than or equal to the 95th percentile for age and sex. There was no difference in obesity by sex. Obesity increased with increasing age groups. The highest prevalence of obesity was among non-Hispanic Black and Hispanic children. While non-Hispanic Asian children had a lower prevalence of obesity than other race and Hispanic origin groups, obesity decreased with increasing family income.

Dental caries in childhood was defined here as untreated or restored dental caries in one or more primary or permanent teeth. 46% of children aged 2 through 19 had dental caries. There is no difference in dental caries by sex. Dental caries increased with increasing age groups. Hispanic children had the highest prevalence of dental caries among children. And dental caries decreased with increasing family income. For hypertension, the estimates are based on a different methodology than those previously published for NHANES. Prior NHANES hypertension estimates have used an auscultatory protocol for blood-pressure measurements. During 2017 through 2018, both an auscultatory protocol, which utilizes a manually obtained blood pressure with a mercury sphygmomanometer, and an oscillometric protocol, which utilizes an automated machine to obtain blood pressure, were used. However, during 2019 through March 2020, only an oscillometric protocol was used. Therefore, blood-pressure measurements and hypertension estimates for the combined 2017-through-March 2020 pre-pandemic data required the use of the oscillometric protocol. The differences in these protocols and a comparison of the blood-pressure values from each protocol are available in a separate Series 2 report from NCHS.

We define hypertension here as meeting any of the following three conditions: a mean systolic blood pressure of greater than or equal to 130 millimeters of mercury, a mean diastolic blood pressure of greater than or equal to 80 millimeters of mercury, or taking a medication to lower blood pressure. Again, the blood pressure measurements were taken using an oscillometric protocol. During 2017 through March 2020, 45.1% of adults had hypertension. More men had hypertension then woman. Hypertension increased with increasing age. And Non-Hispanic Black adults had a higher prevalence of hypertension than other race and Hispanic origin groups.

We found that 41.9% of adults had obesity, defined as a body mass index greater than or equal to 30 kilograms per meter squared. There was no difference in obesity by sex or by age. Non-Hispanic Black adults had the highest prevalence of obesity. Non-Hispanic Asian adults had a lower prevalence of obesity than other race and Hispanic origin groups.

Severe obesity was defined here as a body mass index of greater than or equal to 40 kilograms per meter squared. During 2017-from-March 20, 9.2% of adults had severe obesity. More women had severe obesity than men. Severe obesity was less common in those aged 60 and above, compared to those aged 20 to 39, and those aged 40 through 59. The prevalence of severe obesity was highest among non-Hispanic Black adults, and the least among non-Hispanic Asian adults. Severe obesity was lowest among those with a family income of greater than 350% of the federal poverty level.

Diabetes was defined here as having previously been given a diagnosis of diabetes, having a fasting plasma glucose of greater than or equal to 126 milligrams per deciliter, or having a hemoglobin A1C greater than or equal to 6.5%. Fasting sample weights were used to calculate these estimates.

14.8% of adults had diabetes. The prevalence of diabetes was higher among men than women. The prevalence of diabetes increased with increasing age but decreased with increasing family income and the prevalence of diabetes was lower in non-Hispanic White adults compared to other race and Hispanic origin groups.

Complete tooth loss among adults aged 65 years and older was defined here as having no natural tooth, dental root fragment nor implanted tooth and was based on 28 teeth, excluding third molars. The prevalence of complete tooth loss was 13.8%. The prevalence did not differ by sex but did increase with age. Tooth loss was higher among non-Hispanic Black adults than non-Hispanic White adults but otherwise did not differ by race and Hispanic origin and tooth loss decreased with increasing family income.

So with regards to the future, more data releases are anticipated. These data releases will occur in several different forms. Other combined 2017-through-March 2020 pre-pandemic data are expected to be released on the NHANES website and would be treated like a probability sample. And provided sample weights should be used for analysis with these data.

In the future, this data would be released on the NHANES website along with the currently available data, which can be found under the NHANES 2017 through March 2020 Pre-pandemic data page.

In some cases, 2017-through-March 2020 pre-pandemic data determined to have disclosure risk will be released through the NCHS Research Data Center to ensure additional measures to protect confidentiality. For these data, which are treated like a probability sample, the provided sample weights should also be used for analyses.

For those data released as limited access data files, once released, information about the variables will be available on the NHANES website under limited-access files, under the 2017-to-March 2020 Pre-pandemic data page. However, the actual data will only be available through NCHS’s Research Data Center.

There are some measures that are unique to the 2019-through-March 2020 NHANES data collection. These cannot be combined with 2017-through-2018. And, for these measures, nationally representative estimates are not possible. These data will instead be released through the NCHS Research Data Center.

For these data, released as limited access data files, once released, information about the variables will be available on the NHANES website under limited-access files under the 2019-through-2020 data page. However, again, the actual data will only be available through NCHS’s Research Data Center.

And this can be found on the NCHS website. Information about accessing restricted data, including submission of research proposals, can be found here. Thank you.

HOST:  May has been a busy month, one in which several milestones were observed through NCHS data.  On May 11, full-year 2021 provisional data was released on drug overdose deaths in the country.  Drug deaths topped 107,000 last year, and fentanyl and other synthetic opioids were involved in two-thirds of those deaths.  Overdose deaths increased 15% in 2021, which was half the increase observed in 2020, when overdose deaths increased 30% from 2019.  In 2021, Alaska saw the biggest increase in overdose deaths – a 75% increase for the year.  Hawaii was the only state to have a decline in overdose deaths – a 1.8% drop from 2020.

On May 16, the United States reached a tragic milestone, topping the one million death mark for  COVID-related deaths since January 2020.  COVID-19 remains the 3rd leading cause of death for all Americans.

This month NCHS also documented that the number and rate of marriages in the U.S. during 2020 fell over 16% from 2019, and the number of marriages was the lowest in the country since 1963.  46 states and DC saw declines in marriage during 2020, and only four states – Montana, Utah, Texas, and Alabama – saw their marriage rates increase during 2020.  Nevada, as usual, had the highest marriage rate in the country during 2020 – but the rate dropped nearly 19% from 2019.

On May 24, NCHS released 2021 birth statistics for the nation, showing the first increase in the number of births and the general fertility rate in seven years.  The general fertility rate is the number of births per 1,000 women ages 15 to 44.  The teen birth rate continued to drop in 2021, marking the 28th year in the last 30 years that the birth rate for females ages 15-19 has declined.  While birth rates dropped in 2021 for women between ages 15 and 24, rates increased for women between ages 25 and 49.  Meanwhile, cesarean deliveries increased in 2021, and preterm birth rates also increased, to the highest level since 2007.

And last, NCHS released a report on sexual orientation and differences in access to care, health status, behaviors and beliefs.  The new study drew from three different NCHS data sources:  the National Health and Nutrition Examination Survey, the National Health Interview Survey, and the National Survey of Family Growth.  The research found that bisexual men and women, gay men, and lesbian women report smoking and heavy drinking and using marijuana and illicit stimulants more often than heterosexual people.  Lesbian and bisexual women reported diagnoses of arthritis, asthma, cancer, diabetes, heart disease, and hypertension more often than heterosexual women.  Bisexual women reported having been diagnosed with endometriosis, ovulation or menstrual problems, and pelvic inflammatory disease more often than heterosexual women.  Weight and other body measurements also differed by sexual orientation.

Thank you for tuning in to this month’s edition of “Statcast…”

PODCAST: NHANES Pre-Pandemic Data Release, Part I

April 22, 2022


(Based on the June 16, 2021, webinar, National Health and Nutrition Examination Survey 2017–March 2020 Pre-pandemic Data Release )

HOST: NHANES – the National Health and Nutrition Examination Survey – is designed to assess the health and nutritional status of adults and children in the United States. The survey uses complex sampling design to ensure that the data collected are nationally representative. And it also combines information collected across several different survey components. During a home interview, participants provide information on demographic characteristics, health conditions, and risk factors and behaviors, such as which dietary supplements and prescription medications they are using. Then, participants are invited to travel to a nearby mobile examination center to participate in a health exam, in which they undergo tests, provide lab specimens, and take part in additional interviews. After the exam, participants may be contacted again to participate in post-exam content. This could include activities such as dietary recall, interviews, or wearing a physical activity monitor. The survey content varies over time and covers a wide variety of health conditions and public-health topics. Conducting examinations, along with health interviews, provides data that is invaluable for public health. But it also poses operational and statistical challenges.

Dr. Lara Akinbami, a pediatrician and medical officer with the Division of Health and Nutrition Examination Surveys at NCHS, discussed some of those challenges in a webinar last year:

AKINBAMI: NHANES is conducted in 15 sites per year due to the intricate field operations of the survey. The mobile exam centers, or MECs, must be driven to each new site and set up and maintained according to exact specifications. Teams includes interviewers, clinicians, technicians, and engineers live in the field full time as they travel among the different survey locations over the year. Each MEC contains a mobile laboratory with all the equipment needed for specimen processing and storage until specimens can be shipped to laboratories for testing. On-site testing is also performed for some health measures to provide immediate results to participants. There’s also other equipment for medical testing in the MECs. For example, a spirometer has been used to measure lung function and a sound-isolating room is used to test hearing. Depending on which health exams and measures are being performed, equipment can be swapped in and out of the MECs. The range of pre-pandemic activities that occurred in the MECs was broad. These included body measures, such as weight and height, Blood-pressure measurements, DEXA scans to assess bone density, oral health exams, and phlebotomy and urine collection to collect specimens for a wide array of lab tests. In addition, participants responded to additional interviews, such as audio computer-assisted self-interviews for more sensitive topics that included reproductive health and alcohol and substance use. The MECs provide a way to standardize protocols, equipment, and exam environments across different locations and across time, so that results are comparable. This allows for more accurate interpretation of health differences between groups and of trends over time. NHANES began continuous field operations in 1999.

And, although data collection continued from year to year, data were released in two-year cycles. Each two-year cycle is drawn from a multiyear sample design. These sample designs have changed over time to keep up with changes in the U.S. population. For instance, the 2015-to-2018 sample design selected 60 locations to be visited over four years. The 2015-to-2016 data-collection cycle visited the other 30. Although data are available for two-year cycles, NHANES advises combining cycles together into four-year data sets to calculate reliable estimates for subgroups. For example, estimating the prevalence of a health condition by age group separately for men and women, or for race and Hispanic-origin groups among children, is best done with a four-year data set.

HOST: Dr. Akinbami also discussed in the webinar how the pandemic impacted NHANES data collection.

AKINBAMI: So, like almost everything else, NHANES was affected by the COVID-19 pandemic. The 2019-to-2022 sample design also chose 60 locations to be sampled over four years. NHANES entered the field in 2019 with a plan of visiting the first 30 locations in the 2019-to-2020 data collection cycle. In March 2020, a growing number of cases of COVID-19 disease were being reported to CDC. This suggested that community spread was occurring. Widespread shutdowns had not yet occurred, but the environment was starting to change. For example, mobility data show that, during March, normal patterns and movements started to decline. The NHANES program needed to decide whether continuing field operations posed a risk of coronavirus transmission to participants and staff and their close contacts. On March 16, field operations for NHANES were suspended. And, although it wasn’t clear at the time, this meant that the 30 locations planned for the 2019-to-2020 cycle would not all be visited. When field operations were stopped in March of 2020, the survey had been to 18 of 30 planned locations. And, as 2020 progressed, it was clear that there was no feasible way to resume in-person exams. The potentially long pause before field operations could be resumed raised questions about how a break in data collection would affect estimates of health conditions. Resuming data collection when it was safe to do so would mix pre-pandemic data and pandemic data together and potentially introduce bias into the estimates, especially for a two-year cycle that would have to be extended.

Therefore, it was decided not to collect more data for this cycle. Because no additional data would be collected, the 2019-to-March 2020 sample was not nationally representative. There was no method to create sample weights using the 2019-to-2022 sample design. Additionally, publicly releasing the data for fewer than 30 locations could pose disclosure risks for participants. However, the data that were collected represented a significant investment by survey participants, the federal government, and collaborators; and simply not using the data wasn’t an option. So, a solution was found in the creation of a pre-pandemic data file. The 2017-to-2018 two-year cycle contained a complete sample and was nationally representative. It could be used to build a larger data set. And methodology to combine a probability sample with a nonprobability sample was used but adapted to this situation. The probability sample in this case was the 2017-to-2018 sample. And, rather than a nonprobability sample, the2019-to-March 2020 sample was a partial probability sample, because it was selected based on the 2019-to-2022 sample design.

So here’s an overview of how a 2017-to-March 2020 pre-pandemic data set was created and some analytic considerations when working with the data. The 2015-to-2018 sample design specified the locations chosen for the 2017-to-2018 data collection cycle. And, as we mentioned previously, all 30 locations were visited in 2017 to 2018. The 2019-to-2022 sample design specified 30 locations that were supposed to have been visited in the 2019-to-2020 data collection cycle and only 18 were visited. Combining the 2017-to-2018 sample with the 2019-to-March 2020 sample posed a problem. The 2015-to-2018 and the 2019-to-2022 sample designs were different because the 2019-to-2022 sample design was updated to reflect the changing United States. So the chosen solution was to pick one of these sample designs. Because the 2017-to-2018 data collection cycle fully adhered to the 2015-to-2018 sample design, this design was chosen. The 18 sites that were visited in 2019 to March 2020 were reassigned to the 2015-to-2018 sample design. Now that a design was chosen, the sample weights could be calculated. However, there were still some issues that needed to be resolved. The 2019-to-March 2020 locations didn’t line up exactly with the 2015-to-2018 sample design. The result was that some portions of the country were underrepresented in the data. An adjustment factor was used to equalize representation over the sites visited from 2017 to March 2020. And, once that was done, interview weights and exam weights were then calculated using previous methodology. Extensive assessments confirmed that the final sample was nationally representative by making demographic comparisons to the American Community Survey, which is a population survey administered by the U.S. Census.

HOST: Dr. Akinbami concludes by discussing some important analytic considerations for users of the data.

AKINBAMI: The resulting 2017 to March 2020 pre-pandemic data can be used to calculate nationally representative estimates of health conditions and behaviors. It can be used as the previously released data sets for two-year cycles. However, the data from the partial 2019-to-March 2020 cycle by themselves are not nationally representative.

Therefore 2017-to-2018 data cannot be compared to the 2019-to-March 2020 data. And remember that, because the 2019-to-March 2020 data did not conform to the 2019-to-2020 survey design, no separate survey weights could be constructed for this cycle. It is not appropriate to use the 2017-to-March 2020 pre-pandemic weights for the partial sample collected in 2019 to March 2020. The weight adjustment that was applied to the 2017-to-March 2020 data was designed for overall estimates but not necessarily for subgroups. So, therefore, when 2017-to-March 2020 estimates for subgroups are compared to earlier estimates, trends should be interpreted with caution. For example, when the adjustment factor and other measures were applied to the survey weights, national representation by sex

was achieved and so is representation by age. But some sex-specific age

groups, for example, may have larger variation in estimates depending on how the participants are distributed across survey locations.


HOST: In part two of this feature on pre and post-pandemic NHANES, Dr. Bryan Steirman discusses a published report on health estimates from this NHANES data set.  This webinar is accessible on the NCHS website.

HOST:  On April 12, NCHS released its quarterly mortality data on several leading causes of death, with disease-related mortality rates featured through the third quarter of 2021.  The web feature “Stats of the States” was also updated the same day.  “Stats of the States” features key vital statistics on topics such as Births, Deaths, and Marriages & Divorces by state.  Users can rank States according to rates, either highest to lowest or lowest to highest.  This data visualization was updated with final 2020 data for all these measures.  Included in each State fact sheet are the 10 leading causes of death for each state, which always presents some interesting variation from state to state.  2020, of course, features the introduction of COVID-19 as the 3rd leading cause of death in the U.S.  And at the state level, COVID-19 indeed was the 3rd leading cause of death in 44 states and DC.  As for the other states, COVID was 4th among the leading killers in 3 states:  Alaska, New Hampshire, and Utah.  The virus was the 5th leading cause of death in 2 states:  Washington and West Virginia., as well as the 7th leading cause of death in 2 states:  Hawaii and Oregon, and the 8thth leading cause of death in 2 states:  Maine and Vermont.  Provisional data for 2021 suggests some changes to those rankings, based on regional outbreaks of the virus.

Finally, on April 20th, NCHS released a new report comparing dental utilization rates among adults in 2019 with the arrival of the pandemic in 2020.

Next month promises to be a more active month of data releases for NCHS, including full-year 2021 drug overdose death data, full-year 2021 birth data, and a new report on sexual orientation differences in access to care and health status, behaviors and beliefs.


PODCAST: Alcohol Deaths on the Rise and Suicide Declines

March 18, 2022


HOST:  The month of March is often associated with St. Patrick’s Day, which for some is also an occasion of heavy alcohol use.  NCHS has historically collected data on various health behaviors, including alcohol use, and since the arrival of the pandemic, vital statistics show that there has been a surge in alcohol-induced deaths, an increase from slightly over 39,000 deaths in 2019 to just over 49,000 deaths in 2020 – an increase of more than 25 percent.  Provisional data from 2021 show the number of alcohol-induced deaths have continued to increase, to more than 52,000, up 34 percent from pre-pandemic levels.

Chronic liver disease and cirrhosis is another, long-term adverse consequence of alcohol abuse, and those deaths have increased during the pandemic as well, from over 44,000 deaths in 2019 to over 56,000 deaths in 2021 – an increase of more than 26 percent.  Chronic liver disease and cirrhosis became the 9th leading cause of death of all Americans in 2021, up from 11th prior to the pandemic.

Drug abuse of course is a well-documented scourge in the country, and in March, NCHS released the latest monthly provisional tally of overdose deaths in the U.S., for the one-year period ending in October 2021.  105,752 people died of drug overdoses during this stretch.  Synthetic opioids, primarily fentanyl, accounted for the largest proportion of overdose deaths.

On March 17, NCHS released its latest estimates on emergency department visits in the United States from the National Hospital Ambulatory Medical Care Survey, documenting that more than 151 million ER visits occurred in the U.S. during 2019.

Earlier in the month, NCHS released a new studypdf icon looking at births during the pandemic.  The new report shows that the decline in births appears to have slowed during the first half of 2021, compared to the second half of 2020.  The decline in births during the first half of 2021 would have been even smaller except for a large drop during the month of January.

Finally, NCHS released the latest official trend report on suicide in America.  The latest trends were presented in November in a separate report, and we talked with the author of that report, Sally Curtin, about the latest numbers:

HOST: Despite other causes of death such as drug overdoses and homicides spiking during the pandemic, your data show suicide actually declined, correct?

SALLY CURTIN: Yes that is correct. The number, just under 46,000 in 2020, was 3% lower than in 2019 and also the rate of suicide per 100,000 population was 3% lower as well.  Now, this is actually building on a decline which actually had started before COVID.  There was the first decline in almost 20 years from 2018 to 2019 in suicide – of about 2% – and that’s after an almost steady increase in suicide between about the year 2000 and 2018… it had increased by 35% during that time

HOST: Was it a surprise that suicide dropped in 2020, particularly given the historic increases in homicide and drug overdose deaths?

SALLY CURTIN: That’s a good question because we do know – there’s documented evidence – that some risk factors for suicide definitely increased during 2020.  And some of those risk factors are mental health issues such as depression, anxiety… Also, substance abuse increased during 2020 as well as job and financial stress.  And those are known risk factors for suicide.  So, people were concerned that the actual suicide deaths would increase.  But in the very first sentence of our report we say that suicide is complex and it’s a multi-faceted public health issue.  So it’s not as easy to say, “OK, these risk factors went up for this cause of death; therefore, you know, the deaths are going to go up.”  Suicide is much more complex than that.  There are, as well as risk factors there are elements of, obviously, prevention as well as intervention.  So some of those factors – prevention and intervention – were definitely going on during 2020, and so therefore it’s hard to say and I think in general suicide is just harder to predict than a lot of other causes of death.

HOST: So then would you say that (with) the fact that suicide declined two years in a row, is this officially a new trend?

SALLY CURTIN: It’s hard to say.  I mean, certainly it’s positive in that it’s not continuing to trend upward as it had been for so many years.  But also let me point out it still is historically high – the number is historically high as well as the rate.  They’re both high over the last 20 years.  They’re just a little bit lower than the peak in 2018.  But certainly having two years of declines gives you some hope that it might continue.

HOST: Your new study looked at suicide during 2020 on a monthly basis – what were some things that stood out in your analysis?

SALLY CURTIN: For the most part, in early 2020 – in January and February – the numbers were higher than in 2019.  But starting in March they went lower, and pretty much suicide numbers in 2020 were lower than in 2019 for the rest of the year, except in the month of November where they were just slightly higher.  Now what really stood out is the month of April, where the suicide number in 2020 was 14% lower than in 2019, and that was the greatest percentage difference of any month. And we typically don’t see that big of a change year over year in monthly numbers, so that stood out.  And also it changed sort of the yearly pattern of suicides in general – the month that has the lowest number tends to be in the winter or maybe late Fall but in 2020, April was the month with the lowest number

HOST: That is interesting – would you say that it’s counter-intuitive given that everyone was in lockdown and a lot of people weren’t working etc?

SALLY CURTIN: You would think so and we definitely heard that calls to suicide hotlines just, they just blew up and one study said they went up 800%.  So we do know that people were stressed, but we also know that they were reaching out a lot and so… yeah it is (a surprise) – I think most people will be surprised there was that large drop in April.  And I’ll leave it to others to really sort of explain what was going on – you know, whether everyone was just sort of in shock or if the stigma of maybe reaching out wasn’t quite what it normally is during regular times.

HOST: It looks like the data suggest that the declines were pretty much across the board.  Is that correct?

SALLY CURTIN: Well, for females that’s pretty much correct.  And I mean by race and ethnicity groups – all of the groups for females were lower in 2020 than 2019.  And the greatest percent decline was for Non-Hispanic white females.  There was actually a drop of 10%, and that decline reached statistical significance.  But even for females the declines really started at age 35 and over. For the younger females ages 10 to 34, rates were either the same or actually increased a bit.  For males, there was a mixed picture.  Non-Hispanic white males, as well as Non-Hispanic Asian males, had a decline but groups of minority males had increases.  Non-Hispanic black men had an increase in their rates… Hispanic men… as well as Non-Hispanic American Indian men… And once again, for men, the groups for which there was a decline tended to be in middle-age or older ages, starting with age 35.  It was not apparent in the young people ages 10 to 34.

HOST: The increases among Non-Hispanic black and Hispanic and any other minority group – had these increases been happening prior to 2020 as well?

SALLY CURTIN: Yes, pretty much all of these groups that saw those increases from 2019 and 2020 had been trending upward.  The difference is for white and Asian, they had also been trending upward but now they’ve turned.  So yes, it was just a continuation of a generally upward trend.

HOST: Do you have any indications that the decline in suicide is continuing in 2021?

SALLY CURTIN: So far we do not have any provisional data for 2021 and something that is brought out in the report is that we don’t typically do suicide reports with provisional data because unlike other causes of death it can take longer to get an accurate cause of death saying that it’s suicide.  An example is in the context of a drug overdose.  Often, they have to do toxicology analysis to figure out if the intent was actually suicidal or if it was just accidental.  So for that reason suicide figures tend to lag behind other causes of death and unfortunately right now we don’t have any numbers at all for 2021.

HOST: OK, well any other points to add?

SALLY CURTIN: I think just you know that the overall decline – it’s probably unexpected or for a lot of people because there were known increases in risk factors.  But to just point out once again that although there was an overall decline, this was a lot driven by what happened with the majority group, with Non-Hispanic whites who have among the highest rates and the numbers of suicide.  So the fact that Non- Hispanic white women were down 10%, Non-Hispanic white men were down 3% , it sort of drove the overall decline.  And there were some groups that just did not experience declines – in fact, they experienced increases.  In particular, Hispanic men had an increase of 5% and that did reach statistical significance, but there were also increases for Non-Hispanic black men and Non-Hispanic American Indian men.  So it is encouraging that the overall rate declined, but we certainly need to continue to be vigilant and to realize that this decline was not experienced by everyone.

HOST: Alright, thank you Sally for joining us.

SALLY CURTIN: Oh sure.  Thank you.

PODCAST – Q & A on 2020 Maternal Mortality Data

February 23, 2022


HOST: NCHS kicked off the month of February with the latest annual report on Births in the country, using final data from 2020.  Most of the data were already reported in the provisional 2020 report last May, but there are a few topics that did not appear in that report.

For example, cigarette smoking during pregnancy.  The new report shows nearly 6% of women smoked at some point during their pregnancy in 2020, which was an 8% decline from 2019.  Multiple births in the country have dropped as well.  The twin birth rate in 2020 was down 8% from its high in 2014, and the triplet and higher order multiple birth rate was down 9% from 2019.

NCHS also updated its state-by-state life tables, using data from 2019.  The report showed Hawaii and California had the highest life expectancy of any state.  Hawaiians and Californians are expected to live nearly 81 years, according to the 2019 data.  Mississippi had the lowest life expectancy of any state – 74.4 years at birth.

Two new reports using National Health Interview Survey data from 2020 looked at variations in Health Insurance coverage by geographic and demographic factors.  The studies focused on adults between ages 18 and 64.  The geographic study showed that four states – Georgia, Florida, Texas and North Carolina – had uninsured rates among adults that were higher than the national average.  This report also showed that another four states – New York, Pennsylvania, Michigan, and California – had uninsured rates among adults that were lower than the national average.

Meanwhile, in the demographic report, the data show that nearly 1 in 10 or 31.6 million people of all ages were uninsured at the time of the interview. This includes 31.2 million people under age 65. Five percent of children under 18 were uninsured, and 14% of working-age adults ages 18–64. Nearly 2/3 of people under age 65 were covered by private health insurance, and over half were covered from employment-based coverage.   Four percent were covered by exchange-based coverage, a type of directly purchased coverage. Among people under age 65, about 2 out of 5 children and 1 out of 5 adults were covered by public health coverage, mainly by Medicaid and the Children’s Health Insurance Program or “CHIP.”

In other NCHS news, the February release of provisional data on drug overdose deaths in America featured improvements in the timeliness of the data.  Since the monthly releases began in September of 2017, there has been a lag of six months in the data.  However, beginning with the February 2022 release, that lag has been tightened to only four months, so this new release features data from the one-year period ending in September 2021.  The trends, however, remain the same; drug overdose deaths in the U.S. continue to rise, driven by overdoses from fentanyl and other synthetic opioids.

NCHS also updated its marriage and divorce rate tables in February.  Though NCHS hasn’t collected comprehensive statistics on marriage and divorce since the 1990’s, the Center does post annual tables both nationally and by state on the number of marriages and divorces per 1,000 population.  As in years past, Nevada had the highest marriage rate in the nation, more than twice the rate of the next highest state, Montana.  Wyoming had the highest divorce rate per 1,000 in the country, edging out Alabama.

NCHS also has a new report coming out this week showing that 1 in 10 children under age 18 live in households that had food insecurity in the past month, using data from the 2019-2020 National Health Interview Survey.  Non-Hispanic Black children and Hispanic children were more than twice as likely as non-Hispanic white children to live in households experiencing food insecurity in the past month.

Finally, NCHS released new 2020 data on maternal mortality in the U.S.  The new data show that in 2020, 861 women in the United States died of maternal causes, compared with 754 deaths in 2019.  The maternal mortality rate for 2020 was 23.8 deaths per 100,000 live births, compared with a rate of 20.1 in 2019.  The rate for non-Hispanic black women was significantly higher than for Hispanic women and non-Hispanic white women.

For several years, NCHS had paused its collection of maternal mortality statistics due to data quality issues, but the Center resumed collection of these important data in 2018, and the first data in (11 years) were released in January 2020.  At that time we had a Statcast discussion with Robert Anderson, the chief of Mortality Statistics at NCHS about the data quality issues in the past, as well as the new collection efforts.  Here is a snippet of that conversation:


HOST: Now, with maternal mortality there’s a whole back story – can you share that with us?

ROBERT ANDERSON: Yeah, it’s sort of a long and involved process that we’ve gone through over the last decade and a half or so.  So in the past, as we’ve collected data on maternal deaths – and here we’re talking about years prior to 2003 in particular – research had shown that we tended to underestimate maternal deaths.  And so in order to address that issue, we felt that adding a checkbox item to the death certificate asking whether the decedent was pregnant or recently pregnant was a good idea.  And so we revised our standard death certificate – this is the standard that the states use to base their own state death certificates on –  we revised that to include this checkbox item.  So that was implemented in 2003 but only in a few states. Unfortunately, not all states implemented at the same time and so over the next, well, decade and a half – a little bit more than that actually – we had states implementing gradually this checkbox item and as a result that we saw increases in maternal mortality.  And it got to the point that in 2007, we decided that we couldn’t adequately interpret what was going on and so we stopped reporting maternal mortality altogether, waiting for all of the states to get onto the standard certificate at which point we planned to resume.  So the final state implemented the checkbox item in mid-year 2017, so 2018 is the first data year for which we have data from all states that is based on that checkbox.  So we decided we needed to do an evaluation though, of the data because research post 2003 showed that there were some problems with the checkbox – some errors that were evident.  And so we did this evaluation and we found indeed there were some problems and so we had to come up with a new method to code maternal mortality that would mitigate those errors.  So with the 2018 data we’re now releasing a figure that we believe reasonably represents the risk of maternal mortality in the United States.

HOST: Can we say that the maternal mortality deaths and the maternal mortality rate increased over time?

ROBERT ANDERSON: Well, we can’t really say that with any sort of certainty.  We do know that the increases that we’ve seen compared to the older data that we released, the increases that we’ve seen are largely – mostly even – due to implementation of the checkbox.  They don’t appear to be real increases.

ROBERT ANDERSON: We did an analysis based on 2015 and 2016 data.  The purpose of that particular analysis was to look at the effect of the checkbox on maternal mortality and what we found was that there was a dramatic increase in the number of maternal deaths detected as a result of using the checkbox.  And we also found that that increased very dramatically by age, so at the older ages, the checkbox increased the number of maternal deaths detected by quite a lot.

HOST: So the checkbox you feel then is giving a clearer picture of what the scope of the problem is?

ROBERT ANDERSON: I wish I could say that was the case – we feel like it is definitely allowing us to detect maternal deaths that we weren’t able to detect before.  That said, we know that there are some errors in the checkbox and we’re not entirely sure why these errors are occurring.  This is something that we’re going to be exploring over the course of the next year.  We’re trying to sort that out so we can actually correct it.  But the effect of these errors on the checkbox is that we are finding deaths to women who were not pregnant but for whom that the checkbox was checked that they were pregnant.  And some of these women are quite old actually – beyond reproductive age.

HOST: So when did you start uncovering those problems along this process?

ROBERT ANDERSON: Well, we didn’t actually discover this.  There were some states that were doing their own research on this – the state of Texas, for example, did some important research and they found errors.  CDC’s Division of Reproductive Health did some work with four states recently, that they recently published, that showed that this was the case as well.  And so we were really taking the results of that research, along with our own evaluation, to determine what was going on.

HOST: What else have you found – are there any geographic patterns that suggest maternal deaths are more prevalent in certain parts of the country?

ROBERT ANDERSON: Well, we can’t really say much about maternal mortality by state or by region. Unfortunately, we really don’t understand very well the variation in data quality from state to state. The numbers get quite small and it’s difficult to make judgments based on small numbers – the death rates, mortality rates, get to be very unstable with small numbers.

HOST: So some have been saying or arguing that the problem has been getting worse over time, that even now we don’t have a complete picture.  What would you say to that?

ROBERT ANDERSON: Well, I would agree that we don’t have a complete picture. The evidence that we’re seeing suggests that the problem isn’t really getting worse, but it doesn’t appear to be getting better either.  And that’s, uh, that’s something to be concerned about.  We have data from maternal mortality back to 1915 and we saw substantial declines – they’re really dramatic declines, we’ve seen dramatic decline since then and in recent decades the rate has been rather flat in comparison.

HOST: So one of these new reports looks at a 20 year period prior to the 2018 data. Could you talk about that?

ROBERT ANDERSON: Sure.  As part of our evaluation we did this initial study based on the 2015 and 2016 data to get a sense of the impact of the checkbox and that was based on actual data that we had, we recoded not using the checkbox and then compared it to what we had with the checkbox.  This other study was a little more involved and involves some statistical modeling, and so what we wanted to do with that study was to get a sense for what things would have looked like had all of the states implemented in 2003.  So that was the goal and so we have this trend based on these statistical modeling procedures that shows a fairly stable trend .

HOST: The second report was more focused on the years 2015 and 2016 – can you talk about that work?

ROBERT ANDERSON: Sure.  Yeah, the report based on the data years 2015 and 2016 is really an evaluation of the effect of the checkbox.  And those years were chosen because those were years for which we had data coded without the checkbox.  So we took these data, assuming no checkbox existed, and then we compared that with the data that we had that included the checkbox to get a sense for, to evaluate the effect of the checkbox on the maternal mortality.

HOST: Looking forward, are there any more initiatives underway in terms of improving this whole process and the quality of the data?

ROBERT ANDERSON: Yeah, there’s a lot of, a lot more work to do, really.  I mean, we have to understand better why these errors are occurring in the checkbox.  It may have something to do with electronic registration systems in the way they’re configured.  We’re not really sure, but what we really need to understand if we’re going to correct these errors – we really need to understand why they are occurring and so that’s something that we’ll be working on over the course of the next year.   In addition, we need to work with states and our plan is to do this, to work with states to investigate deaths to women of reproductive age to determine if a pregnancy or recent pregnancy was a factor in their death and this is this can be done using some data linkage to look in birth records and fetal death records for evidence of a pregnancy. I think we can glean a lot of information if we just, you know, take the time and effort to go and look and see.  What we have to do is, we have to work with the states to do this because they are the keeper of those records. They’re the ones that will have to do it and if we can support them in those efforts then hopefully we can get information that will feed back into the vital statistics system and provide us with better data in the future.

HOST: Robert Anderson, thank you for joining us.

PODCAST: The Record Increase in Homicide During 2020

October 8, 2021


HOST: When analyzing trends among leading cause of death (as well as other health measures), it’s important to note that a statistically significant change from year-to-year, whether it be a percent increase or a percent decrease, usually ranges somewhere in the single digits.  So, for example in 2019, death rates from Septicemia dropped nearly 7 percent from 2018, making it the second biggest decline among all leading causes of death.

Occasionally, the one-year change will hit the low double digits.  Death rates from influenza and pneumonia fell 17 percent in 2019, the result of a mild flu season in comparison with a severe flu season the year before.  A double-digit change really stands out as significant when analyzing trends from year to year.

This is why the 30 percent increase in the U.S. homicide rate during 2020 is so remarkable.  The increase itself was not unexpected – after all, the FBI’s Uniform Crime Report had documented a similar increase just days before NCHS released its provisional quarterly estimates on October 6.  But the 30 percent jump in homicide in 2020 was the biggest one-year increase in over a century, with the lone bigger increase coming way back in 1905, essentially a statistical blip that was likely the result of changes to the national death registry at a time when the National Vital Statistics System was first being constructed.

Prior to 2020, the biggest increase in the national homicide rate came in 2001, the year of the September 11 attacks, when the rate increased 20 percent.

Joining us today to discuss this somewhat stunning increase, is Robert Anderson, Chief of the NCHS Mortality Statistics Branch.

Dr. Anderson, thanks for joining us.  When you first saw the number – the 30 percent increase in homicide – what was your reaction?

ROBERT ANDERSON: Well it was it was a pretty big surprise overall.  Now, not as big a surprise it might have been – as you know the FBI had recently released information that suggested nearly a 30% increase, so from that perspective we expected that the increase would be large but 30% is still sort of huge increase in terms of mortality.

HOST:  In terms of statistical history, how does this one-year change historically with other one-year changes, either major increases or major declines, in leading causes of death?

ROBERT ANDERSON:  Well for homicide we did see a pretty substantial increase in 2001 and of course that was directly due to 9/11, to the terrorist attacks that year.  Generally, we don’t see large increases like this for mortality.  You have to go back to when infectious diseases were really prevalent to see large increases for causes of death. I mean, in terms of homicide prior to 2001 you had to go all the way back to the early 1900s – 1904 to 1905 – to find a larger increase than what we saw from 2019 to 2020.  Although that’s likely, at least partly, artifactual due to increases in reporting in the number of states reporting and there’s some other things going on as well at that time that could explain the increase, but mainly it’s an artifact of reporting.

HOST:  So then that 1905 increase – is that even comparable to what we’ve seen here in 2020?

ROBERT ANDERSON:  Not really.  At the time there were maybe 20 states reporting and the number of states reporting was increasing at that time.  Not only the number of states but also the completeness of reporting was increasing in the states that were already reporting as well.  We didn’t have all states reporting in the United States with regard to vital statistics until 1933.  So anything prior to 1933 we would be missing some records and ideally the rate would be sort of reasonably representative for the United States but we know that some of the states coming on board at that time had higher homicide rates overall than the states that were already in the system.

HOST:  So while the increase in 2020 was probably the largest in history the actual rate itself – the number of homicides per 100,000 – is lower than at other points in history more recently.  Could you expand on this?  What period was the peak homicide rate in the country?

ROBERT ANDERSON:  Sure.  So the homicide rate that we’re seeing for 2020 is about 7.8 per 100,000 and it’s a big increase from 6 per 100,000 and 2019 but if you go back to the early 80s and actually in the 70s, you had rates of higher than 10 per 100,000, so at those times you had a higher homicide rate.  Not the big increases or big decreases at that time but the overall level was much higher.

HOST: Death certificate data don’t provide any details about societal issues that may have contributed to the increase, so there’s no way to look at the role the pandemic played in this, if any, correct?

ROBERT ANDERSON:  Yeah that’s essentially correct. With the death certificate data, you really would need to bring in more information.  And I know that there are folks currently looking at this issue to try to understand better the role of the pandemic in this increase, but with death certificate data solely then we really can’t make those determinations.  You really have to look at other patterns and there certainly seems to be a correlation between the two but as we know correlation is not causation.  It’s going to require some I think fairly intensive research to try to sort it all out.

HOST:  In the past, there have been some other studies that have drawn a link between economic downturns and increases in homicide.  What can you tell us about that?

ROBERT ANDERSON: Well there certainly has been some research and the argument is that when economic times get tough, people – crime rises and along with property crime rises, violent crime as well. The correlation though between economic downturns and increases homicide isn’t a perfect one – the correlation is actually fairly weak. It seems to be more correlated with activities that tend to foster violence.  So you saw fairly large increases during prohibition. In the mid 70’s and early 80’s you had big increases and in the drug trade so I think that the connection is more with illegal activity in general rather than economic downturns per se although that does seem to definitely have an impact.

HOST:  And to reiterate, nothing like that on the death certificate?

ROBERT ANDERSON:  No.  The research, they’re looking at patterns using multiple data sets so they can use the final statistics datasets to look at homicides, but they are also using economic data and other sort of social data to model increases and decreases.

HOST:  Could you talk a little bit about the differences between the data released by NCHS and the data in the Uniform Crime Report released by the FBI recently?

ROBERT ANDERSON:  Sure.  So the FBI data is a system where the FBI asks law enforcement agencies across the country to report certain types of information.  Homicides are part of that.  It’s a voluntary system, not all law enforcement agencies report.  The vital statistics data, of course, is coming from the death certificate.  Death certificates have to be filed for every death that occurs in the United States, so vital statistics data are more complete than the data that come out in the Uniform Crime Report.  That said, the trends match pretty closely between the UCR and the vital statistics data so you know when we see something come out in the UCR – like a big increase like we saw with homicide, – there’s a good bet that the vital statistics data will show that as well.  And that’s indeed what we’ve seen.

HOST: Do you expect these provisional numbers to hold up when the 2020 are finalized in the next couple months?

ROBERT ANDERSON:  Yeah the data are complete enough at this point that we’re confident that there won’t be any significant changes between now and when we release the final data.  So the numbers will be pretty close – they are pretty close to final now.

HOST: Is it too early to get a sense of whether this increase in homicide has continued into 2021?

ROBERT ANDERSON:  Yeah it really is because homicides typically require a death investigation.  Information on the cause of death comes to us later than is typical for deaths.  Generally, we get the fact of death and the cause of death in a reasonably timely fashion, within a few weeks at most of the date of death, but with homicides – and this is true for suicides as well and for drug overdoses generally, since an in-depth investigation has to be done and the cause of death may not come till months later and some jurisdictions may take six months for things like toxicology to be complete and the full investigation to be done.  So there’s necessarily a greater lag for causes such as homicides and suicides and drug overdoses, and things like that – deaths that require a lengthy death investigation. And so at this point we have data through the end of 2020 and those data are reasonably complete, but the data for 2021 are really not very complete at this point. We will be releasing some information for 2021 in the coming months but we just don’t have a sense yet for whether homicides are continuing to rise in 2021.

HOST:  Any other things you’d like to add?

ROBERT ANDERSON:  Well I think it is interesting that we’ve seen this large increase in homicides, large increase in drug overdose deaths, and that those seem to be correlated with this big increase in COVID-19 – of course, well COVID-19 was going from zero to 700,000 deaths.  I think for 2020 it’s you know about 350,000 or 370,000,000.  But this is sort of a strange time, I guess, from the standpoint of mortality statistics, I mean, this is just not the sort of thing that we typically see.  We’re usually talking about relatively small increases in mortality or small decreases in mortality.  We don’t normally see these big jumps.  As we go and as we calculate the official mortality statistics for 2020, we’re going to have a lot more work than we normally have to describe what’s going on.  We’re going to need to spend some significant time on these conditions, and these diseases that have increased so much during the pandemic.

HOST:  Strange days.


HOST:  Thanks very much, Dr. Anderson.

ROBERT ANDERSON:  Alright – thank you.

HOST: The new data on homicide show there was a wide difference in the 2020 rates based on geography.  The states with the highest homicide rates were:  Mississippi, Louisiana, Alabama, Missouri, Arkansas, South Carolina, Tennessee, and Maryland.  The District of Columbia had a higher homicide rate  than any state.  The states with the biggest rate increase in 2020 were Montana, South Dakota, Delaware and Kentucky, while only two states, Alaska and Maine, had definitive declines in homicide rates.

Homicide is one of 21 leading causes of death that are included in the quarterly provisional data release that posted this week.  The new numbers are featured on a data visualization dashboard on the NCHS web site.  Some of the significant findings include:

  • A nearly 17% increase from 2019 to 2020 in death rates from accidents or unintentional injuries.
  • Death rates from Diabetes also increased nearly 17%, from the one year period ending in March 2020 to the same point in 2021.
  • Hypertension mortality increased nearly 16% in the one-year period ending in Quarter 1 2021.
  • And death rates from Influenza/Pneumonia dropped 17% during this period.

In other news, this week NCHS also released a report on mortality and marital status in the United States.  The report focused on adults age 25 and up, covering the period 2010 though 2019.  The study found that death rates for married adults during roughly the last decade  have declined by more than three times that of never-married or divorced adults.  Suicide was found to be among the ten leading causes of death for never-married and divorced people, but not among the leading killers for married or widowed people.  Cancer is the number one cause of death for married adults whereas heart disease is the leading killer for unmarried adults.

There are a number of other data releases in the queue for NCHS this month as well.  The National Health Interview Survey is releasing two new reports on October 20th, on mental health treatment among adults and social and emotional support among adults.  Both reports feature data from 2020.

In the area of vital statistics, the latest quarterly provisional estimates on infant mortality, featuring data through 2020, will be released on October 14.  The day before that, the NCHS vital statistics team will release the lastest monthly estimates on drug overdose deaths in the U.S., though March of 2021.  Later in the month, on October 26, there will be a study on 2019 data on fetal mortality  in the United States.  And the following day there will be the latest in the series of rural-urban health studies, this one focusing on rural-urban differences in death rates from unintentional injuries among children.

Also, two methodological studies from the National Health Care Survey will be released on October 18, one focusing on “enhancing identification of opioid-related health outcomes,” and another on “machine learning for medical coding.”

Finally, October is dedicated to several health observances, including Sudden Infant Death Syndrome Awareness.  SIDS is the 4th leading cause of infant death in the United States, according to the latest final data from NCHS.

October is also Breast Cancer Awareness Month.  Over 42,000 women died from breast cancer in the United States in 2019, according to the latest NCHS data.

Join us next month for another NCHS “Statcast,” which will include new studies on suicide by month and demographic characteristics for 2020, as well as a study on mortality among the American Indian/Alaskan Native population.

PODCAST: The 2020 Decline in Life Expectancy

July 21, 2021


podcast-iconHOST:  In February, we had a discussion with Elizabeth Arias with the NCHS Division of Vital Statistics about life expectancy in the United States during the first half of 2020, right as the pandemic was taking hold.  Americans lost a full year of life expectancy during that first part of 2020.  Today we feature the sequel to that conversation, as this week NCHS is releasing full-year life expectancy estimates for 2020.

HOST:  Can you tell us if life expectancy dropped more in the second half of 2020 than in the first half?

ELIZABETH ARIAS: Yes it did – life expectancy declined an additional amount during the second half of 2020 and it did so more for some groups than for other groups.  For example, for the Hispanic population it declined an additional 1.1 years.  For the non- Hispanic white population it declined an additional .4 years and for the non-Hispanic black population it declined an additional .2 years.

HOST:  So overall what was the total decline in life expectancy for 2020?

ELIZABETH ARIAS: It was 1 1/2 years.

HOST: So it’s another half year of decline from the first half then?

ELIZABETH ARIAS: That’s right.

HOST:  Were you surprised it didn’t drop more than 1.5 years given how bad the pandemic became near the end of 2020?

ELIZABETH ARIAS:  No. I was not surprised because the number of excess deaths would have had to be even larger than they were for the decline to have been greater.  And in addition half a year is a substantial amount – it sounds like a small change, but in terms of the way that mortality changes over time which is rather gradual, and it has been gradual and consistent ever since the 1940s, for example.  We have seen an increase gradually increase in life expectancy year to year, and of course a gradual decrease in mortality year to year.  So a half a year is substantial, so if we would have added another year of decline that would have meant that the number of deaths were even greater than what we saw.

HOST: OK so you mentioned some of the declines among race Hispanic groups- what about declines among men versus women?

ELIZABETH ARIAS:  We have seen the gap in life expectancy between men and women decline over the decades.  It started out rather large at the beginning of the 20th century, with women having higher mortality and lower life expectancy than men – that was mainly due to high rates of maternal mortality.  And then we saw over time men having higher mortality and women having greater advantage in terms of life expectancy.  Over time we’ve seen that this change and particularly during the latter part of the 20th century and early part of the 21st century.  The main reason for the decline in the gap, in the difference between the two, has been that life expectancy has been increasing at a faster pace or rate for men.  In other words, men had been catching up to women, and what happened in 2020 with the pandemic is that men experienced higher mortality than women did, and so they basically lost some of what they had achieved during the previous decades.

HOST: Now are you planning to release mid-year 2021 estimates like you did with 2020?

ELIZABETH ARIAS: That’s a good question and I believe we are. I don’t know definitively.

HOST: With 200,000 plus deaths from COVID-19 so far in 2021, would we expect to see another drop in life expectancy?

ELIZABETH ARIAS: No actually, I think what we would see is a small increase in life expectancy in comparison to what we saw in 2020.  In order for us to see another decline in life expectancy we would have to have a greater number of excess deaths than what we have seen so far.  So I would say that we would probably see life expectancy go up but it won’t return to what it was in 2019.

HOST: Now the drop in life expectancy for 2020 was 1.5 years, and yet way back 100 years ago plus, the Spanish flu pandemic resulted in an 11.8 year decline in 1918.  Why the huge difference?

ELIZABETH ARIAS:  Well, you have to think about number of deaths during the Spanish influenza.  So there were over 600,000 deaths, and also you have to think about the size of the population then.  It was a significantly smaller population than what we have today. So you know in 2020 we had 385,000 deaths and a population of over 330 million and back in 1918 we had over 600,000 deaths and – I don’t remember the number of the population at the time – but it was a lot smaller than it is so that translates into much larger death rates and as a result a greater decline in life expectancy.

HOST:  Are there any plans to down the road look at vaccination and deaths from COVID or vaccination and life expectancy?  Anything planned along those lines?

ELIZABETH ARIAS:  That would be really interesting and I don’t know if we would have the data for that. I think if the National Health Interview Survey asks that question – if people, you know, were vaccinated – or the NHANES… And since we link those surveys to our mortality data, we may be able to look at mortality by vaccination status.  But from our data, from vital statistics – in other words from the death certificate – we would not be able to see that.  We would have to have some sort of data that’s linked to our mortality data.

HOST:  OK well thanks for talking to us again Elizabeth.

ELIZABETH ARIAS:   You’re welcome.  Thank you.


HOST:  Through the week ending on July 14, there have been 213,413 COVID-19 deaths recorded on death certificates in the United States during this year.  Deaths occurring in nursing homes or other long-term care facilities have declined from 22% of all COVID deaths in 2020 to 13% of the total so far in 2021.  81% of deaths in 2020 were among people age 65 and up; that percentage has dropped slightly in 2021 to less than 77%.  Deaths in the 45-64 year age group have risen from 16.6% of all deaths in 2020 to over 20% in 2021.  Total excess deaths in the U.S. since February 1, 2020 have topped 663,000, with approximately 80% or more of those deaths due to COVID-19.