Disparities in Maternal and Neonatal Outcomes by Race/Ethnicity

Transcript

• 00:00I. Good evening my friends.
• 00:03Welcome, it says it's a special night
• 00:06for the Yale Pediatric Ethics program.
• 00:08We are hosting along with the yellow
• 00:10program for biomedical ethics.
• 00:12A special session tonight
• 00:13with Doctor Rammers Kaiser.
• 00:14My name is mark material and I am the
• 00:17director of the Pediatric Ethics Program,
• 00:19an I welcome you on behalf of that,
• 00:22as well as the program for biomedical ethics.
• 00:24Are associates, directors,
• 00:25Jack Hughes and Serra Hall,
• 00:27and our manager, Karen Cove,
• 00:29who was sitting very still in the corner
• 00:31of frame of your of your zoom picture.
• 00:34I. Of these these sessions,
• 00:37the way they go to remind you
• 00:39those of you who are new,
• 00:40we will hear from our guest speaker
• 00:42for about 45 minutes, plus or minus.
• 00:45After her talk is over,
• 00:46I'd invite you to submit questions
• 00:48and will have what amounts to a
• 00:50conversation in the zoom aerials.
• 00:51Submit your questions in the chat.
• 00:53I will take a look at those and
• 00:55share those with amorous an also
• 00:57I'll be monitoring this session.
• 00:59I'll ask cameras and then she will respond.
• 01:01Then we will have a bit of a conversation.
• 01:04That way there will be a hard stop.
• 01:06At 6:30 I'm so I apologize if I
• 01:08don't get all your questions in,
• 01:10but I will stick to that agreement
• 01:12that we will end on time and that I
• 01:15may go very quickly 'cause I think
• 01:17it's going to be a very nice session.
• 01:19I want to introduce you an old
• 01:21friend of mine who is Doctor Amris.
• 01:23Kaiser Doctor Kaiser is an assistant
• 01:25professor of Pediatrics in the
• 01:26division of Neonatology at Johns
• 01:28Hopkins University School of Medicine.
• 01:29She's also the medical director of the
• 01:31Neonatal Intensive Care Unit at the
• 01:33Bayview Medical Center at Johns Hopkins.
• 01:35She received her undergraduate
• 01:36degree in the History of Medicine.
• 01:38At the University of Chicago and her.
• 01:42Anne and her medical degree from Mount Sinai.
• 01:45She did pediatric residency
• 01:46at Vanderbilt and of course,
• 01:48did a fellowship in neonatal
• 01:50perinatal medicine here at Yale.
• 01:52So this is her triumphant
• 01:53return to Yale well yell.
• 01:55She did some wonderful work over
• 01:57to school of Public Health.
• 01:59And in her research interests,
• 02:01which are her interests are in the perinatal
• 02:04Epidemiology and health disparities,
• 02:06where she works to elucidate the
• 02:08complex interactions between genetics,
• 02:09environmental context,
• 02:10maternal age and racial ethnic background
• 02:12that drive both outcomes and disparities?
• 02:15And so I've invited to amorous to
• 02:17come here tonight and she kindly
• 02:19accepted to speak to what about
• 02:21those disparities in outcomes for
• 02:23maternal and neonatal patients?
• 02:25And with that I want to turn
• 02:28the floor over to my friend.
• 02:30From Johns Hopkins,
• 02:31and most importantly,
• 02:32this is the best part about the
• 02:34teaching that we do here and everywhere
• 02:36is we get to see the students in
• 02:38the trainees that we work with
• 02:40go off and do wonderful things.
• 02:41So we're very proud of Amerson.
• 02:43Very glad that she made time
• 02:45to speak with this
• 02:46for a bit. Deceiving Doctor Kaiser,
• 02:48please take it away. Alright,
• 02:50well Doctor Mario, thank you so
• 02:51much for such a warm welcome.
• 02:53Give me just a moment to share my screen.
• 02:57Alright. So thank you so much for
• 03:05sending the opportunity for me to be
• 03:08here this evening and to talk with
• 03:10folks a little bit about a topic
• 03:13that's near and dear to my heart,
• 03:15which is disparities in maternal immune.
• 03:17It'll outcomes by race, ethnicity,
• 03:19and really trying to dig into that.
• 03:22Whoops Hold on,
• 03:26I'm having some technical difficulties.
• 03:31There we go OK so just ship to frame.
• 03:38To frame our conversation this evening,
• 03:40I really thought about this more as an
• 03:44opportunity to provide some context and
• 03:46background about kind of the general
• 03:49epidemiological trends in maternal
• 03:51and neonatal adverse birth outcomes,
• 03:54and with that context to try to engender
• 03:58a conversation as we move into thinking
• 04:01about issues of disparities in these
• 04:04trends an in rates of things like
• 04:08maternal morbidity, maternal mortality.
• 04:09Preterm birth low birth weight
• 04:11and infant mortality.
• 04:13And so as a as I,
• 04:15I invite the conversation,
• 04:16but kind of is an overview and
• 04:19preface to this conversation I
• 04:21open with this statement that,
• 04:23compared to their white peers,
• 04:24minority women, especially black women,
• 04:26by also including Hispanic,
• 04:28American Indian, an Alaskan native women,
• 04:30are two to three times more likely
• 04:32to experience adverse maternal
• 04:34and neonatal pregnancy outcomes.
• 04:36That is,
• 04:37there's a huge body of research that
• 04:39has evolved and grown that demonstrates
• 04:42this time and time and time again,
• 04:44and it's a very interesting phenomenon,
• 04:47and we grapple with why that is.
• 04:50So he in this talk I would like to
• 04:52explore the literature that describes
• 04:55epidemiological population level
• 04:56trends and disparities in maternal
• 04:59morbidity and maternal mortality.
• 05:00Preterm birth, low birth,
• 05:02weight and infant mortality.
• 05:04And then after we kind of lay the
• 05:07groundwork with that for context,
• 05:09I want to talk a little bit more
• 05:11about the hypothesis that has been
• 05:13developed to begin to understand
• 05:15why disparities by race ethnicity
• 05:18in these different outcomes exist.
• 05:20And persist.
• 05:23OK,
• 05:23so we're going to start out with
• 05:27some contemporary statistics.
• 05:28We're going to start in the maternal
• 05:32realm and then move into the infant room.
• 05:36Kind of follow it.
• 05:38Follow that process.
• 05:40So in terms of maternal mortality,
• 05:43so it is a devastating occurrence.
• 05:46It is a devastating outcome,
• 05:48an extremely upsetting and problematic
• 05:50for all those who were involved.
• 05:53However,
• 05:54it's important to think about it
• 05:57and contextualize it in terms of
• 06:00its actual incidence and frequency,
• 06:02and thankfully it's a relatively rare event.
• 06:06In 2018,
• 06:06the most recent year in which
• 06:09National Statistics were available,
• 06:10it was documented that there
• 06:12were 658 maternal deaths,
• 06:14which is concerning is upsetting.
• 06:16But that's also in the context of almost
• 06:193.8 million births in that same year.
• 06:22So again, the incidents is very,
• 06:24very low.
• 06:25It's high acuity,
• 06:26and there's a lot of implications for
• 06:29for the occurrence of a maternal death.
• 06:32So then,
• 06:33if the incidents is relatively low,
• 06:35why are we so compelled to really
• 06:37dig into it and figure out what's
• 06:40going on and what's driving it?
• 06:42Well, I think that there are a number
• 06:45of factors that that drive that,
• 06:47and one of the biggest factors is
• 06:49that rates of maternal mortality
• 06:51in the United States are higher
• 06:53than in other developed countries.
• 06:55Specifically, our return mortality
• 06:56rate is 17.4 maternal deaths per
• 06:58100,000 live births, and again,
• 07:00that's the most recent statistics that were.
• 07:03Released in 2018.
• 07:04But when you compare that rate to our peers,
• 07:08were doing a lot worse,
• 07:10so we're anywhere from you know,
• 07:121 1/2 to five to six times.
• 07:15It's happening more frequently in
• 07:17the United States than it is in use.
• 07:20Other developed countries that
• 07:22we consider to be our peers.
• 07:24And so thinking about that in looking
• 07:27at that, we know we can do better.
• 07:30We rank 47 out of 184 countries.
• 07:33At The Who derived internal
• 07:36mortality statistics back in 2015,
• 07:38and we have so much space to
• 07:41improve and we know we can do it.
• 07:45The second consideration is that
• 07:47the rates and maternal mortality
• 07:50in the United States appear to be
• 07:53increasing while concomitantly the
• 07:55rates in some of our peer countries
• 07:58have fallen and continue to fall.
• 08:02Here is a graph that just demonstrates
• 08:05overtime the maternal mortality ratios,
• 08:07and you can see that they certainly
• 08:10do begin to rise in the early 2000s
• 08:14and continue to do so even today.
• 08:17I say that they appear to rise
• 08:19because there is some question as
• 08:21to whether or not this increase in
• 08:24maternal mortality is driven more
• 08:27by data collection considerations.
• 08:29Back in 2003, there was consensus statement.
• 08:32Look forward to change the death
• 08:34certificate in the way that it
• 08:37collected information about maternal
• 08:39mortality to standardize the process
• 08:41and make the data more accurate.
• 08:43Unfortunately,
• 08:44because that was rolled out and
• 08:47implemented across all 50 states
• 08:49over a span of almost 15 years,
• 08:51there was a lot of variability in
• 08:54how the data was collected and the
• 08:57veracity of the data was questionable.
• 08:59So much so that the National
• 09:02Center for Health Statistics.
• 09:03I just stop calculating their maternal
• 09:07mortality statistics for a period of almost
• 09:1010 years because of the issues with the data.
• 09:14So again,
• 09:14we see this statistic.
• 09:16We want to address it,
• 09:17but there is a little bit of uncertainty
• 09:20as to whether or not maternal mortality
• 09:23ratios are actually increasing.
• 09:25But I would argue that most
• 09:27concerningly about our maternal
• 09:29mortality rate is that when maternal
• 09:32deaths are reviewed by external
• 09:34maternity mortality review committees,
• 09:37nearly 2/3 of those committees
• 09:40deemed the deaths preventable,
• 09:42and so if that's the case,
• 09:45we have no excuse to not address this
• 09:48head on and to really find our way
• 09:53in helping to improve the lives of.
• 09:56Mothers and infants and all
• 09:59those around them.
• 10:01I also just want to make note
• 10:03as you may have suspected,
• 10:05that in terms of maternal
• 10:07mortality rates and statistics,
• 10:08there are definitely wide racial ethnic gaps.
• 10:11Unfortunately, minority women and black
• 10:13women are non Hispanic black women as I
• 10:17refer to them from this point forward,
• 10:19having incredible burden placed upon
• 10:21them wherein they are up to three times
• 10:24as likely to die from privacy related
• 10:27cause as white women are and I've put
• 10:29some of the statistics down there.
• 10:32For you, this is very worrisome
• 10:34that there is such a huge divide,
• 10:37and even though this is an event
• 10:39that doesn't occur frequently,
• 10:41the burden is really shouldered
• 10:43by certain groups,
• 10:44and we owe it to them to figure
• 10:46out what's driving the disparities
• 10:48and to create interventions that
• 10:51are specifically tailored for them
• 10:53so that we can begin to close that
• 10:56gap and assure good health for all.
• 10:58I think it's interesting to note
• 11:01also kind of in Devane.
• 11:03Differences by race in maternal
• 11:05mortality that the top causes of death
• 11:09are not consistent across all women.
• 11:12Mini stratified by race.
• 11:13We find that non Hispanic black
• 11:16women that the top causes of death
• 11:18amongst that group is cardiomyopathy
• 11:21and cardiovascular conditions.
• 11:23However, among non Hispanic white women,
• 11:25mental health conditions account
• 11:27for the number one cause of death.
• 11:31And I will take this moment to mention
• 11:34that this is such an important
• 11:36topic to study and to research,
• 11:38but it can be very challenging because
• 11:41the incidents is so low and because
• 11:43of that the sample sizes are small,
• 11:46it can be very difficult to understand.
• 11:48Further,
• 11:49stratify your analysis to understand
• 11:50what's going on within individual groups.
• 11:53We see a perfect example of that.
• 11:55Yeah,
• 11:56right here in that Hispanic women
• 11:58there is insufficient data.
• 11:59The numbers are too small for us to.
• 12:02Figure out with the top cause of
• 12:05death for that an ethnic group is.
• 12:07Then I also want to mention that the
• 12:10leading causes of death we talked
• 12:12about top causes of death by race,
• 12:15but top causes of death also vary by
• 12:18the time at which the death occurs.
• 12:20So for mothers who passed away within
• 12:23the 1st two weeks after delivery,
• 12:25the top causes of death are
• 12:27postpartum hemorrhage.
• 12:28Hypertension in sepsis.
• 12:29However,
• 12:29for mothers who are able to make it
• 12:32through that immediate postpartum
• 12:34period go on to be discharged
• 12:36from the hospital and go home.
• 12:38The top cause of death among women.
• 12:40Seven days to one year after deliveries.
• 12:43Cardiomyopathy and I just bring that
• 12:45up to kind of further reinforce the
• 12:47idea that we need to understand what's
• 12:50going on with in different populations,
• 12:52so that we can make sure that
• 12:55our screening counseling an
• 12:56interventions are really tailored
• 12:57and so in this particular case,
• 13:00to make sure that clinicians
• 13:01and other medical providers
• 13:03know what they're looking for,
• 13:05what their counseling mothers
• 13:06about to make sure that their
• 13:09interventions are the most effective.
• 13:12So you talked a bit about maternal mortality.
• 13:15Now we're going to move into morbidity.
• 13:18So the concept of severe
• 13:20maternal morbidity as an adverse
• 13:23pregnancy outcome is defined as a
• 13:25woman who receives a life threatening
• 13:28diagnosis or she needs to undergo
• 13:31a lifesaving procedure during
• 13:33the delivery hospitalization in
• 13:35order to kind of standardized what
• 13:38that means a little bit further,
• 13:40the CDC has curated an maintains a
• 13:43list now of 21 identifiers of severe
• 13:46maternal morbidity with associated ICD codes.
• 13:50So that it's a very easy to figure out
• 13:52what they are, and that there's a lot
• 13:55more standardization within the research.
• 13:56Severe maternal morbidity affects more than
• 13:5960,000 lumen per year in the United States,
• 14:03and it's really kind of a warning
• 14:06sign prior to women have experiencing
• 14:09a maternal mortality.
• 14:11So really,
• 14:12really important to kind of think
• 14:15about on that continuum of illness.
• 14:18It is associated with significant
• 14:21disability on cost.
• 14:23Just to give you a sense of what kinds
• 14:25of medical conditions and procedures
• 14:28are used to indicate a severe morbidity,
• 14:31I've listed them here for you and I
• 14:34completely agree when when patients
• 14:36experience these conditions or have
• 14:38need for these kinds of interventions,
• 14:40the acuity and severity of illness
• 14:43is quite high.
• 14:46So just to talk a little bit
• 14:49about the general Epidemiology
• 14:50of severe maternal morbidity.
• 14:53Unfortunately for all women,
• 14:55rates of severe morbidity are increasing and
• 14:59spend a little bit challenging to kind of.
• 15:02Cobble together and arrive population
• 15:04level estimates because there are so many
• 15:07kind of different fragmented data sources,
• 15:09but there are a couple of studies
• 15:12that have come out that use
• 15:14the national inpatient sample,
• 15:16which is a large,
• 15:17impatient database managed by the Agency
• 15:20for Healthcare Quality and Research,
• 15:22which its function is to serve as
• 15:25a representative sample of the
• 15:27population so they purposefully
• 15:28sample from different community.
• 15:30An urban hospitals across the United States.
• 15:33So that researchers are then able to
• 15:36calculate and extrapolate from that
• 15:38smaller sample size to the population
• 15:41level to derive population level estimates.
• 15:44So from this study,
• 15:46it was determined that the overall
• 15:49rate of severe maternal morbidity
• 15:51during a delivery hospitalization
• 15:54increased almost 200% over the
• 15:56time period from 1993 to 2014.
• 15:59There is a complementary study that
• 16:02was conducted by Callahan ET al that
• 16:06found similar increases over a 10
• 16:08year period of 75% in the incidents
• 16:12of severe maternal morbidity's most
• 16:14frequent morbidity was a blood transfusion.
• 16:17And it's really remarkable how
• 16:19much they increased it increased
• 16:22by almost 400% of that.
• 16:24Really drove a lot of the
• 16:26statistics that you're seeing,
• 16:28but it's also noteworthy to mention that
• 16:31there were multiple other severe morbidities
• 16:34that increased by at least 75% over this.
• 16:37Same over that 10 year time period
• 16:40that included acute renal failure,
• 16:43shock from botic,
• 16:44pulmonary embolisms,
• 16:45AR DSQMI aneurysms in cardiac
• 16:48and pericardial surgeries.
• 16:49And then as severe morbidities as
• 16:52kind of harbingers or risk factors
• 16:54for eventual mortality for delivery
• 16:57hospitalizations where there was
• 16:59a severe complication that in the
• 17:02hospital proportionate mortality ranged
• 17:04from not so much to upwards of 33%
• 17:08depending on the specific morbidity
• 17:11that the mother was diagnosed with.
• 17:14So if we've gotten a little bit of the
• 17:16lay of the land about how severe morbid
• 17:20morbidities are increasing overtime,
• 17:22many different factors could
• 17:24be contributing to that.
• 17:25But it's very concerning,
• 17:27and certainly worthy of our attention.
• 17:29And now we're going to turn our
• 17:31attention a little bit to disparities
• 17:33in the incidence of severe maternal
• 17:35morbidity's during the delivery
• 17:38hospitalization specifically.
• 17:39So there's a very elegant study that
• 17:41was done in 2018 by M on colleagues.
• 17:45That use the same national
• 17:47inpatient sample but a smaller.
• 17:49Time period from 2012 2015 to specifically
• 17:52generate population based estimates of #1.
• 17:55The prevalence of chronic physical and
• 17:58behavioral health conditions among women
• 18:00who come in to deliver an and then
• 18:03to the incidence of severe maternal
• 18:05morbidity among those women as well.
• 18:08This is really to understand how
• 18:10the extent of the problem of the
• 18:13issue and then Furthermore they
• 18:16stratified their estimates by race,
• 18:18ethnicity and group folks into.
• 18:20Five or six different categories
• 18:22for the purposes of this talk,
• 18:23I will focus mostly on non Hispanic,
• 18:25white and non Hispanic black women.
• 18:28So they hypothesize that the prevalence
• 18:31of comorbid chronic conditions would
• 18:33be higher among minority women,
• 18:35and they found that to be true,
• 18:38and it was especially true
• 18:40for non Hispanic black women.
• 18:42They also hypothesize that the incidents
• 18:45of maternal severe morbidity would
• 18:47be higher among minority women women
• 18:49compared to non Hispanic white woman,
• 18:52an more pronounced among
• 18:54non Hispanic black women.
• 18:56So they did many fancy analysis
• 18:58with lots of fancy statistics,
• 19:01but at the end of the day they they
• 19:04confirmed both of their hypothesis
• 19:06and found that minority women,
• 19:08and specifically not has been in black women,
• 19:12have a higher burden of disease,
• 19:14as evidenced through higher prevalence
• 19:17of chronic conditions and higher
• 19:19incidence of maternal severe market is.
• 19:22And what's really interesting is
• 19:24they went on to do some additional
• 19:27calculations to figure out basically
• 19:29that the excess burden if you will.
• 19:32So if all women experience the
• 19:34same rates of severe morbidities
• 19:36and chronic health conditions,
• 19:39then we would see a 28% reduction
• 19:42in severe morbidities among
• 19:44racial and ethnic minority women,
• 19:46and that reduction would be even more
• 19:49pronounced for non Hispanic black women.
• 19:52As we've been talking about South 28% at 41%,
• 19:56and in addition for all women they
• 19:59would see about a 15% reduction
• 20:02in severe maternal morbidity.
• 20:04So it's it reinforces that there
• 20:07is a disparity there,
• 20:09but it's also motivating to see how
• 20:12much of a difference in how much
• 20:15of an impact working to mitigate
• 20:19disparity specifically can have.
• 20:21Suggested the summary.
• 20:23Overall trends in maternal morbidity and
• 20:26mortality are concerning on multiple levels.
• 20:29One of the biggest challenges is
• 20:32assuring the quality of data that's
• 20:35being collected and towards that
• 20:37end the CDC and other government
• 20:40institutions have really.
• 20:42Made a point of developing different
• 20:45programs to address that need,
• 20:47because if the quality of the data
• 20:49is not sufficient then we're not
• 20:52going to have accurate understanding
• 20:54of what's going on around us.
• 20:57I think it also shows us that there
• 20:59is a need for immediate intervention.
• 21:03With respect to maternal mortality,
• 21:05because of the high percentage of
• 21:07preventable deaths, if these desperate,
• 21:09deemed, preventable,
• 21:09then there should be no reason why we
• 21:12can't figure out how to prevent them.
• 21:15So that seems like relatively
• 21:17low hanging fruit.
• 21:18And then I would argue that further
• 21:20because of the persistent disparities,
• 21:23there is a need for the interventions
• 21:25to decrease mortality and morbidity
• 21:27to specifically be geared towards
• 21:29black and other minority women to
• 21:32make sure that we optimize the
• 21:34efficacy of the interventions,
• 21:35and in so doing mitigate disparities,
• 21:38we want to have good health for all.
• 21:41And this is 1 Avenue of doing so.
• 21:45So we've talked again about
• 21:47mothers and their adverse outcomes,
• 21:49and now we're going to move into the
• 21:51infant realm and talk about birth
• 21:54outcomes and trans in statistics overtime.
• 21:57So because we're going to be talking
• 21:59about this for a little while,
• 22:01wanted to run through a couple
• 22:03of definitions as in
• 22:04unitologist pre term birth
• 22:05is near and dear to my heart.
• 22:07Makes up a large contingent of the
• 22:10patient population that I care for.
• 22:11This refers to infants who are born at
• 22:13less than 3637 weeks gestation with
• 22:15the normal gestation lasting 40 weeks.
• 22:17Low birth weight infants are those
• 22:19born at less than 2500 grams,
• 22:21which is about 5 pounds, 8 ounces,
• 22:23and the infant mortality is the number of
• 22:26infant deaths per live per 1000 live births.
• 22:28And those deaths occur prior to
• 22:31the infant's first birthday.
• 22:32So prior to 365 days of age.
• 22:36So you've got all these definitions
• 22:38and think about birth outcomes.
• 22:40What's the big deal about pre term birth?
• 22:43Well, I think that we need to
• 22:46kind of contextualize it as well.
• 22:48Pre term birth is the number one cause
• 22:51of infant mortality as it accounts for
• 22:54about 1/3 of infant deaths annually
• 22:56while low birth weight doesn't
• 22:58have quite the same contribution
• 23:00to our impact on infant mortality,
• 23:03it still is a significant risk
• 23:05factor for infant mortality.
• 23:07An an importantly survivors of preterm
• 23:09birth and low birth weight are at risk
• 23:13for complications in early childhood,
• 23:15adolescence,
• 23:15and offload all throughout the life course.
• 23:18So it's very exciting to think about.
• 23:22Decreasing rates of pre term
• 23:24birth to mitigating disparities in
• 23:26preterm birth and low birth weight.
• 23:28Because in so doing will directly
• 23:31drive down your infant mortality rate.
• 23:34But Furthermore you are working towards
• 23:36improving the health of individuals not
• 23:38just during the birth hospitalization,
• 23:41not just during infancy and childhood,
• 23:43but across the entire life.
• 23:45Course is very very important pursuit.
• 23:48Just a little bit of the Epidemiology of pre
• 23:52term birth over the last couple of decades,
• 23:55so we've made strides chipped away at it.
• 23:58But starting in the 1990s,
• 23:59they rated pre term birth began to slowly
• 24:02rise and it did so for about 16 or 17 years.
• 24:06We saw a 20% rise over
• 24:08that time point in 2006.
• 24:10It peaked and then from that point
• 24:13forward began to decline and is to
• 24:15over the next eight years or so.
• 24:18It's worth mentioning that it's a
• 24:21pretty significant decrease in the
• 24:24rate of pre term birth that we see
• 24:26just around 2006 and that was driven
• 24:29in very large part by a concentrated
• 24:32effort within the acceptable community
• 24:34to change their practices regarding
• 24:36elective Caesarean sections prior to term.
• 24:39Previously,
• 24:39the kind of prevailing thought and
• 24:42feeling had been all the baby at 35 or
• 24:4536 weeks is close enough to determine
• 24:47if we need to schedule a C-section.
• 24:50An non medically indicated see
• 24:51section A little bit early.
• 24:53It will be fine.
• 24:54The baby will be fine but not
• 24:56completely recognizing that although
• 24:58the chances of survival were excellent
• 25:01at that gestation elhage that pre
• 25:03maturity brings with it its own
• 25:05set of morbidities and that was
• 25:07not something to be taken lightly.
• 25:09That intervention and practice
• 25:11change was very successful.
• 25:12You can see that reflected on
• 25:14a national level by
• 25:15decreases in the rate of preterm birth.
• 25:18We have had success for a time for time,
• 25:22but since 2014 you can see at the rate
• 25:25is slowly starting to rise and has
• 25:28done so over these past six years and
• 25:31we're now back to pre 2010 levels.
• 25:34So at its peak around 2006 2007
• 25:37pre term birth rate was around 12%.
• 25:40We driven it down to around 9,
• 25:42maybe slightly below that and
• 25:44now we're kind of coming back up.
• 25:472 into the time range.
• 25:51And then we start to think about
• 25:54disparities in rates of pre term
• 25:56birth so that there certainly are
• 25:59African American women have 1 1/2
• 26:01to two times the risk of preterm
• 26:04birth as do non Hispanic white women.
• 26:07Even when you adjust for multiple
• 26:09socio environmental.
• 26:10Another confounding factors.
• 26:11So part so big part over 2 is
• 26:15you're trying to understand what
• 26:17drives these disparities and how.
• 26:20How do how does the magnitude of
• 26:22those disparities change overtime?
• 26:24So this graph demonstrates over the
• 26:27same time period as we look at the
• 26:30trends and overall rates of preterm birth.
• 26:33Looking at the difference between
• 26:35rates in non Hispanic black and
• 26:38non Hispanic white infants.
• 26:39So similar,
• 26:40so thankfully the risk difference
• 26:42has been slowly declining.
• 26:44Since about 2006 and it looks like
• 26:47there's actually been a very nice steady
• 26:50downward trajectory of that risk difference,
• 26:53so that gap was bit by bit
• 26:56coming closer was narrowing.
• 26:58But unfortunately it started
• 27:00to rise in about 2013.
• 27:02This is kind of concomitant with the
• 27:05overall trend in uptick of pre term births.
• 27:09An there is difference has now surpassed 5%,
• 27:13which is above where it was kind of
• 27:16during the height of its decline.
• 27:19If you will.
• 27:20So that is something concerning an
• 27:23warrants further investigation.
• 27:25Overtime to make sure that that
• 27:28trend doesn't continue.
• 27:29OK,
• 27:29so you've talked about pre term
• 27:32birth and we're going to transition
• 27:35to low birth weight.
• 27:37So the trends that kind of overall
• 27:41epidemiological trends in low birth
• 27:44weight has been somewhat similar
• 27:47to pre term birth in that they
• 27:50rose for a period of 15 years,
• 27:53give or take an again by that 20%
• 27:56mark they peaked around 2006.
• 27:59Plateaued and then began to
• 28:02decrease an natured in 2012.
• 28:06But I think the biggest thing
• 28:08to note is that the.
• 28:10The the magnitude of that change is much
• 28:14smaller than what we saw in pre term birth.
• 28:18However, similarly to pre term birth,
• 28:21we are now seeing that rate
• 28:24of low birth weight rising.
• 28:27It's risen 4% in the last seven
• 28:30years and is currently at 8.28%,
• 28:33which is higher than it was.
• 28:36At its peak in 2006,
• 28:39before falling.
• 28:40So again,
• 28:41something that we need to continue
• 28:44to follow and see how this evolves
• 28:46and see what that tells us about.
• 28:49The nature of drivers of disparities.
• 28:52I will also mention on that you
• 28:54can you can see that the risk
• 28:57difference between non Hispanic white
• 28:59and non Hispanic black low birth
• 29:02weight rates is fairly constant.
• 29:04Starks to kind of narrow a little bit,
• 29:08but we're starting to see widening that risk
• 29:12difference in these in the last few years.
• 29:16This is kind of a recapitulation of that.
• 29:20OK, so we talk through kind of
• 29:22trends in preterm birth and low birth
• 29:25weight Epidemiology that they're
• 29:26not exactly the same similar to one
• 29:29another in their overall trends.
• 29:31Overtime, the infant mortality has
• 29:32followed quite a different trend.
• 29:34First and foremost is worthwhile to
• 29:37note that the amount of data and
• 29:39the timeline over which that data
• 29:41was collected is a lot more robust
• 29:44and extensive than what we have,
• 29:46especially your pre term birth,
• 29:47because the statistics have been
• 29:49captured for so long.
• 29:51So we have good statistics starting at
• 29:53the turn of the 20th century actually
• 29:56show the rates for non Hispanic,
• 29:58non Hispanic black infants,
• 30:00and so that we can get a great sense of
• 30:03what the trends have done overtime and
• 30:06what the risk difference has been overtime.
• 30:09So the overall happy story.
• 30:11Over the entire course of the 20th century,
• 30:14we see a continual decline
• 30:16in infant mortality rate for
• 30:18both black and white infants.
• 30:20However,
• 30:20what is striking is that the risk
• 30:24difference really didn't budg with the
• 30:27entire first half of the 20th century,
• 30:31and it may have widened at
• 30:34subsequent to that point,
• 30:36so there is 2 fold greater infant
• 30:39mortality rate for black newborns
• 30:42compared to white newborns,
• 30:44and it has really maintained that
• 30:47magnitude of difference if not widened.
• 30:50Despite advances in the treatment
• 30:52and prevention of disease and
• 30:54advances in sanitation, housing,
• 30:56public health interventions,
• 30:58and that trend continues even to the most
• 31:02recent statistics published in like 2017.
• 31:05So in summary,
• 31:06thinking about trends in birth outcomes,
• 31:09unadjusted trends in pre term birth,
• 31:11low birth weight,
• 31:12an infant mortality rate are similar,
• 31:15but they're not interchangeable.
• 31:17As we discussed.
• 31:18I think really,
• 31:19what what always strikes me is
• 31:21how little variability there is
• 31:24in low birth weight overtime.
• 31:26How much more variability,
• 31:28comparatively infrequent birth,
• 31:29there has been overtime,
• 31:31and while both preterm birth and
• 31:33low birth weight look like they're
• 31:36starting to tick up a little bit.
• 31:39Infant mortality rate continues to decrease.
• 31:41As we noted that despite overall
• 31:44decreases in the crude rates
• 31:46of all three of these.
• 31:51Disparities persist across all three
• 31:53birth outcomes and the magnitude of
• 31:56the difference between rates by race.
• 31:59Ethnicity hasn't changed
• 32:00meaningfully over that time,
• 32:02at all, so we've done well with
• 32:05improving health kind of globally.
• 32:08But we've not done well in
• 32:11addressing this persistent disparity.
• 32:13And as I mentioned earlier,
• 32:15it's interesting to note that
• 32:17the disparity persists even after
• 32:19adjustment for traditional risk factors,
• 32:21and So what that brings to
• 32:24mind for me is to say, OK,
• 32:27so if we adjust for all of these
• 32:30different risk factors and it
• 32:32doesn't make a difference that
• 32:34there's still this excess risk.
• 32:37There is unmeasured risk we haven't
• 32:39been able to account for it,
• 32:40so our job really is to try and
• 32:43figure out what is that unmeasured
• 32:45risk and how do we account for it.
• 32:47But because it's kind of a. So complex.
• 32:51The greater question to ask is
• 32:54how do we conceptualize the risk?
• 32:57Do we think about risk as individual,
• 33:01individually identifiable risk factors?
• 33:02Do we think about combinations of
• 33:05risk factors? Groupings of exposures?
• 33:07Are we thinking about social context?
• 33:10Are we thinking about?
• 33:13Biologic influences?
• 33:14Or are we thinking?
• 33:16Are we taking a step back and
• 33:19thinking about frameworks
• 33:22for conceptualizing the risk?
• 33:25And so that's what we're going to
• 33:28talk about a little bit more right now,
• 33:31so we're now going to move in now that
• 33:34we've kind of explored a little bit
• 33:36the existence of an persistence of
• 33:39disparities in poor birth outcomes.
• 33:42Overtime we're going to talk through
• 33:44the different hypothesis that have
• 33:46been put forth to try to explain and
• 33:49contextualize these disparities in
• 33:50adverse pregnancy and birth outcomes.
• 33:53With the focus is really on my birthday.
• 33:56Pumps
• 33:59So there are many, many of them
• 34:01come from the social Sciences,
• 34:04and many of them have been
• 34:07around for many many years,
• 34:09and so that's where I'm going to start
• 34:13with weathering hypothesis that was
• 34:15originally developed in the late 70s,
• 34:18early 80s by Doctor Arlene Geronimus,
• 34:21who is at the University of Michigan.
• 34:24Ann. She was trying to think
• 34:27about an explanation for.
• 34:294 two kind of simultaneous observations.
• 34:32One was the excess infant mortality
• 34:35rate among black infants and the
• 34:38other was why the teenage pregnancy
• 34:41rate among non Hispanic black
• 34:44teenagers was markedly higher than
• 34:47among non Hispanic white teenagers.
• 34:50The prevailing thought at the time was
• 34:54that teenagers have an increased risk
• 34:57of poor birth outcomes that included
• 35:01pre term birth and low birth weight,
• 35:04which then kind of are perpetuated
• 35:07into infant mortality that within
• 35:10the African American community there
• 35:13was a higher incidence or higher
• 35:17percentage of women of childbearing
• 35:19age who were teenagers having babies.
• 35:22That it was these teenagers who accrued
• 35:26the excess risk an who were really
• 35:29driving the excess infant mortality
• 35:32rate because of because of the risk
• 35:35associated with with teenage birth. She.
• 35:41Did not buy that an actually thought.
• 35:45Quite the opposite.
• 35:47She was struck by the.
• 35:50Perpetual.
• 35:51Social disadvantage that many
• 35:53women within African American
• 35:55community we're experiencing,
• 35:57and she thought that it was actually
• 36:00the older women and the oldest women
• 36:03and not the younger or youngest
• 36:05women who were accruing the increased
• 36:08risk of poor birth outcomes,
• 36:10which was then translating
• 36:12into excess infant mortality,
• 36:13and that was older women that
• 36:16were driving that disparity.
• 36:18So her original hypothesis was at
• 36:21the health status of black women
• 36:24begins to deteriorate earlier.
• 36:26Specifically, in young adulthood,
• 36:28as a consequence of prolonged exposure
• 36:31to social and environmental disadvantage.
• 36:34Because or or in concert with this
• 36:37earlier deterioration of health status.
• 36:40Reproductive health also suffers
• 36:42and begins to deteriorate earlier
• 36:44as well as more rapidly among black
• 36:47women compared to white women.
• 36:50And this in turn results importer
• 36:52birth outcomes at relatively earlier
• 36:55ages for black but not white women,
• 36:58and that this then propagates a
• 37:00widening of disparities in poor birth
• 37:03outcomes with advancing maternal.
• 37:05Age.
• 37:06Now keep in mind that the original
• 37:09application in the original outcome
• 37:11in this study was infant mortality
• 37:14and the original population to
• 37:16which it was being applied.
• 37:18Was African American women and and
• 37:21this was the hypothesis to explain
• 37:24disparities in infant mortality rates.
• 37:26It's a fascinating hypothesis.
• 37:29There's a lot of investigators who
• 37:32have taken it an investigated it
• 37:35and applied it to different datasets
• 37:38an it's really come into its own
• 37:41and to be accepted.
• 37:44Mainstream hypothesis,
• 37:45but in in that process of
• 37:49evaluation it has been expanded.
• 37:53From From an explanation for
• 37:57disparities in infant mortality,
• 38:00to be applied as an explanation
• 38:03for differences in any health
• 38:06outcome by race ethnicity.
• 38:08So instead of justice African
• 38:11American women experiencing this now
• 38:14it's any African American person.
• 38:16With any health outcome
• 38:19where there is a disparity,
• 38:21Anet has Furthermore been more
• 38:24broadly generalized to apply to any
• 38:27marginalized or minority population to
• 38:30explain disparities in health outcomes
• 38:33compared to the majority population.
• 38:36So it's interesting to see that evolution,
• 38:40but I think it it does beg the question.
• 38:45Is this hypothesis inappropriate?
• 38:49Explanation for.
• 38:51The existence of health disparities
• 38:53in in all of these different
• 38:55contexts and applied to all of
• 38:57these different populations.
• 38:58Or do we need to be very thoughtful about?
• 39:02Evaluating two what populations?
• 39:06This can be applied.
• 39:10So her moving kind of from from
• 39:12the social Sciences a little bit
• 39:15into the Biological Sciences and we
• 39:17start to talk about allostatic load.
• 39:20I like to talk about this next because
• 39:22it's kind of the biological objective
• 39:25measurement counterpart to weathering.
• 39:27So the concept of allostatic load
• 39:29is that this is this concept is
• 39:32representative of the cumulative
• 39:34wear and tear on the body's systems.
• 39:37That is 02 repeated adaptation to stressors.
• 39:40I do want to emphasize that this
• 39:43is wear and tear that is due to
• 39:46not to the stressor itself,
• 39:48but to the body's reaction to your
• 39:50adaptation to this Dressler stressor.
• 39:53We think about Al static load
• 39:55as the physiological burden
• 39:57that's imposed by stress,
• 39:58and it can be kind of quantified
• 40:01and indicated by thinking bout
• 40:03two categories of biomarkers.
• 40:05Do you get your primary mediators or
• 40:07biomarkers in your secondary mediators?
• 40:10The primary media?
• 40:11Are biomarkers are physical substances
• 40:14at the body releases in response to
• 40:17stress and the secondary mediators
• 40:20are the effects that the body.
• 40:22Feels from the release of
• 40:24those primary mediators,
• 40:26so the example of being a primary
• 40:28mediator might be epinephrine
• 40:30that your body is releasing in
• 40:32response to a stressful situation,
• 40:35and the secondary mediator would
• 40:37be an elevated blood pressure in
• 40:40response to epinephrine release.
• 40:42Outside it,
• 40:43load is operationalized as a numerical score.
• 40:46Some scale of zero to 10,
• 40:49a score of three to four correlates with an
• 40:52increased risk of morbidity and mortality.
• 40:55An, as I mentioned previously,
• 40:57this this approach is really
• 40:59able to quantify.
• 41:00I would argue the concept of weathering.
• 41:03There's no built into weathering.
• 41:05There was no objective measurement.
• 41:07There's no way to measure.
• 41:10Its effect,
• 41:11its extent,
• 41:12but being able to develop the outside
• 41:16load score as kind of the numerical
• 41:20representation of weathering.
• 41:22OK.
• 41:22So will then move into thinking about
• 41:26the life course perspective as a
• 41:30framework for understanding disparities,
• 41:33and this one has really come into its
• 41:36own in the last couple of decades is
• 41:39really kind of an integrative approach,
• 41:42so the the idea of a life course
• 41:45perspective is that early life
• 41:48experiences have the ability to
• 41:50shape health not only in the moment
• 41:53but across the entire lifetime.
• 41:56And potentially across generations
• 41:58within the life course perspective,
• 42:00there is an emphasis.
• 42:02The timing and duration of
• 42:04experiences and exposures and the
• 42:07importance of when things happen and
• 42:10that is because kind of thinking.
• 42:13A development in a developmental
• 42:15context that there are critical
• 42:18periods of development in the lives
• 42:20of all of us and they coincide with
• 42:24times when there's a lot of growth,
• 42:27development, and activities so that
• 42:29things like during fetal life during
• 42:32the first months, two years of.
• 42:34Infancy and childhood,
• 42:35when the rate of growth and formation
• 42:38of GNU connections and all these
• 42:40different things are going on
• 42:42and then we have another period
• 42:44during adolescence and puberty.
• 42:46When that happens again.
• 42:48So the the purpose of having
• 42:50particular attention to the timing
• 42:53and duration of these early life
• 42:55experiences is that the magnitude
• 42:58of the effect of the experience,
• 43:00positive or negative,
• 43:01can change based on whether it
• 43:04happens during a critical period
• 43:06of development or outside of that
• 43:09period of development and the effect
• 43:11of these different experiences is to
• 43:14change the health trajectory overtime.
• 43:16So thinking about the health trajectory's.
• 43:18As I've malleable and responsive
• 43:21entity that will change in reaction to
• 43:25different stressors and exposures an
• 43:28it's this conception that really helps
• 43:31us to think about adult health outcomes.
• 43:35ANAN Health later in life as being
• 43:39intimately connected with the early life
• 43:42experiences and the importance of thinking
• 43:45back when you are trying to understand.
• 43:49Why there might be?
• 43:52Differences or disparities in
• 43:54outcomes that present in older age
• 43:58that that you were risk factors.
• 44:01Protective factor could be very remote from
• 44:06the the manifestation of health or illness.
• 44:10In addition,
• 44:11of course,
• 44:11protective also explicitly considers
• 44:13the role of social context,
• 44:15not just at one point in time but
• 44:17overtime and how the how that ongoing
• 44:20context and changes in context can
• 44:22shape and shift health trajectories.
• 44:25And this is again particularly
• 44:28relevant when we're thinking
• 44:31about the childhood or early.
• 44:34Early shaping of health and disease
• 44:36trajectories over the life course
• 44:39and the incidence of chronic disease.
• 44:44So we kind of talked about these
• 44:47different frameworks that really come
• 44:49out of the social Sciences tradition.
• 44:51We haven't talked as much about
• 44:54the hard Sciences and so one of the
• 44:58additional considerations that I
• 44:59wanted to be sure to bring into this
• 45:03conversation when we start to think
• 45:05about how do we frame explorations
• 45:08for understanding disparities in
• 45:10health outcomes is genetic factors.
• 45:12Now I know that there are.
• 45:15Strong opinions on both sides
• 45:17about where genetic factors lie,
• 45:20but I think that there is a very
• 45:23strong argument to consider genetic
• 45:26contribution when evaluating
• 45:28disparities in health outcomes.
• 45:30An for me, birth outcomes specific
• 45:33to disparities in reset.
• 45:35Pre term birth,
• 45:37we know that there is variation in
• 45:40certain characteristics like broccoli and
• 45:43just stational age between populations.
• 45:46And at this May in fact
• 45:48influence birth timing.
• 45:50In addition,
• 45:51we know that there's a a genetic
• 45:53component or a strong genetic component
• 45:56to birth timing in that a prior history,
• 45:59either personal or familial,
• 46:01of pre term birth increases risk.
• 46:03So if a mother has had a
• 46:06previous pre term birth,
• 46:08she's at increased risk for having
• 46:10a subsequent preterm birth,
• 46:12and similarly if she herself
• 46:14was born pre term,
• 46:16she has an increased risk
• 46:18of having a pre term birth.
• 46:20Or if she has a family member such
• 46:24as the sister who was born pre term,
• 46:28she also has an increased risk
• 46:30of delivering a preterm baby.
• 46:33In addition,
• 46:34heritability studies of pre term
• 46:36birth have demonstrated that.
• 46:3820 to 40% of the variability in
• 46:40preterm birth can be attributed to genetics,
• 46:43so it seems like.
• 46:46For looking looking at associations between.
• 46:51Genetics and pre term birth.
• 46:53Broadly that there is a strong case to
• 46:56be made that genetics play a factor.
• 46:59So if we think that you guys can play
• 47:02a factor in birth timing and pre term birth,
• 47:06could it also play a role in
• 47:08drive in driving disparities in
• 47:10pre term birth and birth timing?
• 47:12It's interesting to note that in
• 47:15Genome wide Association studies when
• 47:17they've been stratified by race,
• 47:18ethnicity and and there is an analysis of.
• 47:21Which single nucleotide polymorphism's
• 47:23or which genetic variants are
• 47:26associated with pre term birth?
• 47:27Those may or may not be the same
• 47:30for different populations that
• 47:32are defined by race ethnicity.
• 47:34It's been challenging though,
• 47:36because the results have been very
• 47:39difficult to reproduce and we are.
• 47:41We are understanding more and more
• 47:44that individual variance produce
• 47:46a very small magnitude of affect,
• 47:48so you may need to have a lot of.
• 47:51A lot of variance to have to have the
• 47:55manifestation of a very small effect.
• 47:58And then there's also the additional
• 48:01challenge of the skepticism of
• 48:04sufficient homogeneity among self
• 48:06reported African Americans in in
• 48:09conducting these genetic studies
• 48:11and how much.
• 48:13Heterogeneity is there due to
• 48:16mixing between folks of African
• 48:20ancestry and European ancestry.
• 48:23So all that being said,
• 48:25I think it makes the case to say yes,
• 48:28we should consider genetic factors,
• 48:29but it's not a guarantee.
• 48:32So. With all of that in mind,
• 48:37where do we find ourselves right
• 48:39now in terms of understanding
• 48:41and evaluating disparities in
• 48:43health outcomes in birth outcomes?
• 48:46And how can we leverage what we talked
• 48:49about today to make forward progress?
• 48:52So I think. At this point in time,
• 48:57based on the events of these past months
• 49:01and years and all of the work that
• 49:05has gone into helping us to understand
• 49:09what could be driving disparities,
• 49:12it's undeniable that structural racism
• 49:15an other social determinants of health
• 49:18are significant drivers of disparities.
• 49:21We know that the legacy of slavery
• 49:24is still active in our day to day
• 49:27lives and still influencing and
• 49:29informing health all and it has been
• 49:33pervasive in the insidious and very
• 49:35challenging to identify an address.
• 49:38But it must be addressed in
• 49:41order to improve health.
• 49:43So we understand that.
• 49:47External factors,
• 49:49an environment and greater societal
• 49:52structure plays a role.
• 49:55However, it's not clear that that's the
• 49:59only driver an is there still space for
• 50:04other contributors to be investigated more?
• 50:08Thoroughly and rigorously.
• 50:11So I just wanted to talk a
• 50:15little bit about the concept of.
• 50:18Genetics, genomics and personal biology.
• 50:20When it comes to conversations about
• 50:23race and disparities in outcomes by race,
• 50:27so time and time again,
• 50:29we hear that race is a social construct.
• 50:33And so because of that,
• 50:35there's no biological underpinning or
• 50:37no genetic underpinning to that idea,
• 50:40and there's kind of an 1 one side people
• 50:44who feel that race is a social construct.
• 50:48That's all it is.
• 50:50An can't be can't ever be anything more.
• 50:53And then there are kind of a contingent
• 50:57of folks who see race as a potential
• 51:01genetic or biological construct.
• 51:03Slightly different perspective.
• 51:05So if we dig into this idea that
• 51:09race is a social construct,
• 51:11what it means is that conceptually it
• 51:14is fluid and it can change based on
• 51:17socially derived definitions is not fixed.
• 51:20It's not innate,
• 51:21and because of that there is
• 51:24no genetic basis to it.
• 51:27And Furthermore,
• 51:27some would argue that there is
• 51:30no relationship between race and
• 51:32innate biological characteristics,
• 51:34instead arguing that we are all one race.
• 51:38We are all human.
• 51:40And so there are 4, four that viewpoint.
• 51:45There are a few reasons that commonly
• 51:48genetics is rejected as an explanation
• 51:51for disparities in health outcomes.
• 51:54One common one is the observation
• 51:57of the statement that there is
• 52:00greater genetic variability within
• 52:02populations than between populations,
• 52:05and this was really this kind
• 52:08of came to the fore.
• 52:11It was popularized by Richard.
• 52:13We want him back in the 70s who
• 52:16was looking at variation in blood
• 52:18group proteins an he found that 85%
• 52:22of the variation in blood protein
• 52:24types could be accounted for by
• 52:27variation within populations.
• 52:28An races and only 15% by variation
• 52:31across them. So he had taken.
• 52:33He had a large contingent of
• 52:36subjects who he divided into races
• 52:39and then look into see.
• 52:41Ann. If there was a.
• 52:45What the genetic variability was.
• 52:48And not surprisingly,
• 52:49based on that methodology came up with
• 52:52these results and concluded that most
• 52:55variation between humans because of
• 52:57differences between individuals and
• 52:59not differences between populations.
• 53:01So we have that is 1 Parliament.
• 53:04Another reason for the rejection
• 53:06of genetics as an explanation for
• 53:08disparities in health outcomes, I think,
• 53:11is a very real and well founded fear
• 53:15that history will repeat itself.
• 53:18In the past, medicine and science
• 53:23has been used and manipulated too.
• 53:29Create, maintain an propagate hierarchies
• 53:32of worth and lend credence to them from
• 53:38a scientific standpoint or endorsed
• 53:41by scientific principles objective.
• 53:44Objective principles And that.
• 53:50And as has happened,
• 53:52not only was kind of science
• 53:54and medicine manipulated,
• 53:56but then once that manipulation happened,
• 53:59there is complicity on the part
• 54:02of the scientific and medical
• 54:05establishment to stand up against that.
• 54:08Miss Construction of of results
• 54:11are of the science and a concern
• 54:14that if we start to go down this
• 54:17path way of thinking about genetics
• 54:21as drivers of disparities in.
• 54:23Outcomes by race that we might
• 54:26find ourselves back there.
• 54:28And that also in so doing there is
• 54:34D humanization that then results.
• 54:38In or allows for the justification
• 54:41to perpetuate social inequality,
• 54:43which is what we are all fighting so hard to.
• 54:49Get ourselves. Out of and on better footing.
• 54:54And then the last concern is
• 54:56that there is a fear that the
• 54:59characterization of race as a fixed
• 55:01or innate characteristic that cannot
• 55:04be changed absolves responsibility on
• 55:06the part of medical professionals.
• 55:09Investigators on the other stakeholders
• 55:11in society to intervene to improve
• 55:14the disparities.
• 55:14They thought that if there's
• 55:17a genetic predisposition,
• 55:18there's nothing we can do about it.
• 55:21So why try or the idea that?
• 55:24Biology is destiny.
• 55:25Ann and I just bring this up because in
• 55:29in the conversations and interactions
• 55:31that I've had in conversations
• 55:34about disparities and understanding
• 55:37drivers of disparities and talking
• 55:39with folks who come more from a
• 55:43social Sciences training background.
• 55:45There definitely is push back
• 55:48against that idea,
• 55:49and these are some of the concerns
• 55:54or objections that are cited.
• 55:57However,
• 55:57I think there are also reasons to accept
• 56:00genetics as a potential explanation
• 56:02for disparities in health outcomes.
• 56:05I think it's it's very the idea
• 56:07that people of the same race self
• 56:10identified race share common genetic
• 56:12traits or variance is valid and
• 56:15that has to some extent been born
• 56:17out in the scientific literature,
• 56:19and I think we also can't ignore
• 56:22the fact that when we adjust for
• 56:24multiple con founders who try
• 56:26and understand this relationship.
• 56:29And that adjustments fails to account
• 56:31for the disparities in outcomes by race.
• 56:34It opens up the possibility that
• 56:37there's an underlying predisposition
• 56:38towards developing the outcome.
• 56:40That is biologic that is genetic
• 56:42as not to say that that's the
• 56:45entire T of the explanation,
• 56:47but to refuse to entertain
• 56:50that as a possibility.
• 56:51I think is shortsighted.
• 56:54I would Furthermore going to say
• 56:56that in there been some challenges
• 56:59in growing pains in the past,
• 57:02there was alot around the time that the
• 57:05human genome was sequenced completely
• 57:07and there was all this excitement
• 57:10about the endless capabilities of
• 57:12genome candidate gene studies in
• 57:15Genome wide Association studies.
• 57:17In being able to finally help us
• 57:19understand the kind of biologic and
• 57:22mechanistic underpinnings of disease.
• 57:24There was a lot of confidence,
• 57:27perhaps misplaced over confidence in the
• 57:30ability of variation at the genome level,
• 57:33to explain disparities in health outcomes
• 57:36and overtime as it has become clear that.
• 57:40The extent to which genetic variants
• 57:43do not independently cause complex
• 57:45disease is very great that investigators
• 57:47have been humbled and more willing
• 57:50and more accepting and more excited
• 57:52to try to take a step back and say,
• 57:56OK, well if it's not this one
• 57:59genetic variant in and of itself,
• 58:02how do I evaluate combinations
• 58:03between different parts of the genome
• 58:06between different modifications,
• 58:08protein expression, etc etc?
• 58:09How do I evaluate interactions with?
• 58:12The environment.
• 58:13How do we kind of look for
• 58:17those higher level?
• 58:19Interactions an and higher level.
• 58:24Associations between different
• 58:25factors that individually may not
• 58:28give us the answer we're looking for,
• 58:31but collectively may get us there.
• 58:34I think that there's no more of
• 58:36an emphasis on the biology of the
• 58:39individual as dynamic and influenced
• 58:42by the surrounding environment,
• 58:44and there's less emphasis on a fixed
• 58:47genetic code that there are fixed
• 58:50parts and there are mobile parks and
• 58:53we need to investigate both pieces and
• 58:56that Furthermore genetic factors and
• 58:58the contribution of genetic factors
• 59:00to disparities can now be interpreted
• 59:03more broadly and conceptualize more broadly.
• 59:06Not just the genetic code itself,
• 59:09but all of these other again modifiable
• 59:13factors that downstream impact how.
• 59:16That impacted the interactions and
• 59:19reactions with this surrounding environment,
• 59:21so that includes studies of the genome
• 59:25epigenome, the metabolome proteome,
• 59:26transcriptome microbiome, etc etc.
• 59:29Multi omics.
• 59:31So just a couple of parting thoughts.
• 59:36Through the process of preparing
• 59:38this presentation and thinking
• 59:40about these disparities,
• 59:41I was struck again by the thought
• 59:44that complex diseases really are
• 59:46multifactorial and variation in
• 59:48risk is unlikely to be caused by a
• 59:51single factor acting in isolation.
• 59:53So whether that's a single exposure,
• 59:55whether that's a single snook,
• 59:57it's unlikely that that that one piece
• 01:00:01will account for the entire T of what
• 01:00:04we're seeing in terms of the disparities.
• 01:00:07There are lots of different hypothesis
• 01:00:10for understanding disparities
• 01:00:11in pregnancy and birth outcomes,
• 01:00:14and it's important to remember that
• 01:00:16they are not mutually exclusive,
• 01:00:19so there is no need to necessarily
• 01:00:22discount any of these hypothesis upfront,
• 01:00:25but rather to think through them,
• 01:00:28entertain them,
• 01:00:29evaluate them and really try to
• 01:00:32figure out does this hypothesis
• 01:00:35fit in the context of this?
• 01:00:38Relationship and this outcome
• 01:00:39that I'm trying to examine.
• 01:00:42And then I also just wanted to make
• 01:00:45mention of the fact that in the
• 01:00:48United States self identified race
• 01:00:51is reasonable proxy for genetic ancestry,
• 01:00:54and I think that that is the direction
• 01:00:57where folks are moving who really are
• 01:01:00interested in cultivating a multi multi
• 01:01:03faceted multidisciplinary approach to
• 01:01:06evaluating disparities in outcomes.
• 01:01:09While it's true that race
• 01:01:11is a social construct,
• 01:01:13differences in genetic ancestry track
• 01:01:15reasonably well alongside those constructs.
• 01:01:18So in the absence of having
• 01:01:21readily available.
• 01:01:22Gene typing for all it seems a
• 01:01:25reasonable proxy to use for race
• 01:01:28as a proxy for genetic ancestry
• 01:01:30while recognizing its limitations
• 01:01:32and the absence of absolutes.
• 01:01:35And it's interesting to note also
• 01:01:38that self identified African Americans
• 01:01:41in the United States derive about
• 01:01:43on average 80% of their genetic
• 01:01:46ancestry from enslaved Africans.
• 01:01:48So although there is a lot of
• 01:01:51conversation about admixture,
• 01:01:52and certainly that percentage
• 01:01:54changes and fluctuates.
• 01:01:56Based mostly on geography and where
• 01:01:58in the United States you are.
• 01:02:01Again it lends additional credence
• 01:02:03to the idea that self identified
• 01:02:06race can be used as a reasonable
• 01:02:09proxy for genetic against ancestry.
• 01:02:12And ultimately,
• 01:02:13that by staying open to all these
• 01:02:16different possibilities and new
• 01:02:18ideas as a researcher,
• 01:02:20you have the opportunity to
• 01:02:22leverage all of this knowledge and
• 01:02:25all of this power to help,
• 01:02:28to disentangle in understand drivers
• 01:02:30of disparities in birth outcomes.
• 01:02:33Thank you very much.
• 01:02:35Wow, Amherst, that was it.
• 01:02:37That was
• 01:02:38an amazing talk. Thank you very much.
• 01:02:40I'm sure there's going to be.
• 01:02:42There's already some questions lined
• 01:02:43up and I'm sure if you want to ask,
• 01:02:46but I'd like to take my moderators
• 01:02:48prerogative and ask the first question
• 01:02:50if I understood you correctly.
• 01:02:51You spoke about how the usual
• 01:02:53demographic things that we started
• 01:02:55to try and explain the disparity
• 01:02:57didn't pan out as the cause of those.
• 01:02:59If we control for things like income,
• 01:03:01education, etc.
• 01:03:02That that we still see the
• 01:03:04disparity that was.
• 01:03:05That was your point, so.
• 01:03:06What an and in in putting
• 01:03:08together all the things you said,
• 01:03:10it leads me to wonder,
• 01:03:12can we control for other things?
• 01:03:13We talk about the influence, for example,
• 01:03:15of stressors of environmental stressors
• 01:03:17of the history of racism attrition.
• 01:03:19Is there way to control some
• 01:03:20measure for that?
• 01:03:21Which makes me wonder,
• 01:03:22how does the United States in that
• 01:03:24disparity that black white disparity?
• 01:03:26How does the United States
• 01:03:28compared to other countries?
• 01:03:29Have you know we saw a lot of of usdata,
• 01:03:32but I wonder if other countries that
• 01:03:34perhaps have a different history or
• 01:03:36a different current environment.
• 01:03:37Um, if their disparity is higher or lower,
• 01:03:39or how that looks.
• 01:03:41That's a fantastic question. I have two,
• 01:03:44so it's something that I'm interested
• 01:03:46in really getting into in the future,
• 01:03:49but I have to admit I haven't
• 01:03:51looked at those statistics in
• 01:03:53a really long time, so I don't.
• 01:03:56I don't know that I have a great
• 01:03:58answer for you about kind of
• 01:04:00contemporary outcomes and disparities
• 01:04:02in places like written, for instance,
• 01:04:05so I'm not I'm not sure off hand.
• 01:04:08I do recall from way back that there was.
• 01:04:11A study that was looking at
• 01:04:15risk of preterm birth among.
• 01:04:18Among parents who were not of the same race,
• 01:04:22so they looked at the risk of pre term
• 01:04:25birth for a black mother and a black father,
• 01:04:29a black father and a white mother.
• 01:04:33A black mother and a white father and
• 01:04:36a white mother and a white father.
• 01:04:39And they found that the risk of
• 01:04:41preterm birth was the highest for the
• 01:04:44couple where both parents were black.
• 01:04:46The lowest where both parents were
• 01:04:48white and for the two interracial
• 01:04:51couples the risk was in between.
• 01:04:53The risk was higher when the mom was black.
• 01:04:57And when the mom was white and I
• 01:04:59believe that that study was either
• 01:05:01done primarily or there was a like a.
• 01:05:04Kind of a validation study that was done.
• 01:05:08It was not in this country, but I can't.
• 01:05:11I can't remember if it was Northern Africa.
• 01:05:14I think it may have been Northern Africa.
• 01:05:17This is fascinating stuff.
• 01:05:18Thank you so much.
• 01:05:20I'm going to get to some
• 01:05:21of these questions here.
• 01:05:22I'd invite you folks to put your questions.
• 01:05:25I see summer in chat in summer,
• 01:05:27in Q&A, so going forward,
• 01:05:28go ahead and put your questions in chat,
• 01:05:31but I'm going to look and see some
• 01:05:33stuff that's in the Q&A portion.
• 01:05:35So amorous someone asks,
• 01:05:36excuse my ignorance,
• 01:05:37but what are some examples of
• 01:05:39the environmental disadvantages?
• 01:05:39I think this question came through
• 01:05:41relatively early in your talk
• 01:05:42about the disadvantages that
• 01:05:44could influence the disparity.
• 01:05:46Absolutely, so it's it's many of
• 01:05:49the things that we're talking about
• 01:05:52a lot these days, so it's poverty,
• 01:05:55intergenerational poverty,
• 01:05:56its lack of education,
• 01:05:58lack of access to medical care,
• 01:06:01lack of access to healthy foods.
• 01:06:04All all those kinds of socio
• 01:06:09environmental challenges.
• 01:06:10Concerns about personal safety like
• 01:06:12are you live in a safe environment?
• 01:06:14Are you able to get to work?
• 01:06:17Is that in a safe environment?
• 01:06:19Do you have what kind of transportation
• 01:06:21do you have access to? Is it?
• 01:06:24Are you relying on public transportation?
• 01:06:26An it is stressful to be able to manage that.
• 01:06:29So it's all these kind of different different
• 01:06:31levels and different considerations,
• 01:06:33and it's.
• 01:06:34Yeah, I'll stop there.
• 01:06:36Thank
• 01:06:37you, so here's a.
• 01:06:38It's more of an observation and suggestion.
• 01:06:40Thank you for this overview.
• 01:06:42Doctor Kaiser, I would suggest that
• 01:06:44instead of genetics at the focus
• 01:06:46on researching perinatal health,
• 01:06:48disparities should be on epigenomics
• 01:06:49on how the adverse exposures
• 01:06:51influence gene expression and
• 01:06:52you actually commented on that.
• 01:06:54Briefly, talk about genomics as well.
• 01:06:56And also there are genetic methods
• 01:06:58and platforms to determine ancestry so
• 01:07:01we can control for that in studies,
• 01:07:03even among racial ethnic groups in it.
• 01:07:05Things to my something I thought of when
• 01:07:08you mentioned you want is work in 1972.
• 01:07:10I couldn't help wondering.
• 01:07:11I wonder what level of sophistication he
• 01:07:13had for looking at the genetic variation
• 01:07:15both within groups and between groups etc.
• 01:07:17Absolutely. Absolutely thank you for that.
• 01:07:21I appreciate that feedback. OK,
• 01:07:23now here's some more
• 01:07:24thoughts from your audience.
• 01:07:26Can you comment on Elizabeth how's work
• 01:07:28in New York City that showed that both
• 01:07:31black and white women were at higher
• 01:07:33risk for morbidity and mortality at
• 01:07:35primarily black serving hospitals,
• 01:07:37suggesting that a significant
• 01:07:39tributed contributed to disparities
• 01:07:41is poor quality of care.
• 01:07:43Similarly, could you comment on why
• 01:07:45outcomes in the US are substantially
• 01:07:47worse than other high income countries?
• 01:07:49How are the health systems
• 01:07:50in those countries different?
• 01:07:52How do they do it better?
• 01:07:54ETC so the first part of her
• 01:07:57question related to white women
• 01:07:59and the morbidity mortality being
• 01:08:01cared for it in hospitals that
• 01:08:03primarily sort of black communities.
• 01:08:06Absolutely, so I have read her work an
• 01:08:10she's got kind of a lot of different
• 01:08:13facets to this specific questions
• 01:08:16that she asks in answers. It does.
• 01:08:21Begin to speak to quality of care,
• 01:08:24but I think that there's also
• 01:08:26there also issues of residential
• 01:08:28segregation that may be at play.
• 01:08:31To be honest, I would have to go back
• 01:08:34to that specific article and read a
• 01:08:38little bit more about what her like,
• 01:08:41how the analysis was structured,
• 01:08:43but I appreciate the comment and I
• 01:08:46think that must absolutely there
• 01:08:48there is embedded in all of this.
• 01:08:51Quality of care access.
• 01:08:53If care and variability in
• 01:08:55outcomes by hospital,
• 01:08:56that's its own kind of its own contingent.
• 01:08:59An area of research as well.
• 01:09:01And it sounds like this study
• 01:09:03falls into that as well.
• 01:09:05So yes, that's most likely a part of it,
• 01:09:08but how it fits into the.
• 01:09:11The entire T of the context.
• 01:09:13The broader context is a
• 01:09:15little bit challenging to say.
• 01:09:17At this point, thank
• 01:09:18you. Emirates to these studies and
• 01:09:20disparity control for the higher
• 01:09:22incidence of hypertension and obesity
• 01:09:24in Blacks compared to whites. Yes. Yes,
• 01:09:29so great that. Here's a
• 01:09:32question for me.
• 01:09:33Here's a question for the modern very nice.
• 01:09:35Will this presentation be available
• 01:09:37after the live web and R?
• 01:09:39And the answer is thanks to our friend,
• 01:09:42Doctor Kaiser? Yes,
• 01:09:42this will be available on the website
• 01:09:45for the program for biomedical ethics.
• 01:09:47If you just go to biomedical ethics at Yale,
• 01:09:50you will find it there very soon.
• 01:09:53OK, another question.
• 01:09:54I think for our speaker,
• 01:09:56if there is a significant
• 01:09:57epigenetic component to
• 01:09:59disproportionate black mortality,
• 01:10:00how can you disentangle that from
• 01:10:02structural racism and the history of
• 01:10:05anti black racism in the United States?
• 01:10:07So there's a pretty easy question so.
• 01:10:10But I mean,
• 01:10:11I'll put an important one affair question.
• 01:10:13This is this is hard stuff
• 01:10:15to China on sort of stuff.
• 01:10:17It's also a little bit frustrating
• 01:10:19how with all the genetic technology
• 01:10:21and data available as well as all
• 01:10:23the demographic data available that
• 01:10:25we still don't have a better answer
• 01:10:27for why this disparity or a complete
• 01:10:29answer for why this disparity exists.
• 01:10:31But perhaps you'd like to.
• 01:10:33Poverty caused by structural racism.
• 01:10:35All that I'm sorry.
• 01:10:36That's the next question should be so
• 01:10:38the last question will get to that
• 01:10:40in a moment. Netex from structure isn't.
• 01:10:43I mean, I think that's a really
• 01:10:46excellent question and I think we're
• 01:10:49at the point where we're only just
• 01:10:51beginning to delve into and beginning
• 01:10:54to ready to here to really hear what,
• 01:10:57how pervasive and what the extent
• 01:11:00of structural racism has been.
• 01:11:02So, I mean, we can point to examples of it,
• 01:11:06but really, understanding the
• 01:11:08entire T of it is going to take.
• 01:11:12A long time and a lot of work and
• 01:11:14I don't know how from where I sit
• 01:11:18right now to begin to dis entangle.
• 01:11:21Epigenetics are from structural
• 01:11:22racism per say.
• 01:11:23It's going to have to be attention to detail,
• 01:11:26attention to the subtlety Anna lot of
• 01:11:29thought about how you structure your
• 01:11:31analysis, an what data set you're using,
• 01:11:33and how you handle that data set.
• 01:11:36It's a great question, but I don't.
• 01:11:39I don't know that.
• 01:11:41I mean there's like that.
• 01:11:43That literature is growing so
• 01:11:45rapidly and it's so bulky to be
• 01:11:48able to delve into it process it,
• 01:11:50synthesize it, and then take.
• 01:11:53From that What you want to apply to inform?
• 01:11:59Analysis about epigenetics.
• 01:12:01It's monumental undertaking.
• 01:12:04Here's
• 01:12:05a question. I think you that you
• 01:12:07you're talking touched on to some
• 01:12:09point in answer to some extent,
• 01:12:11but but I'm curious on your thoughts on this.
• 01:12:14Do you think poverty and low income are
• 01:12:16the underlying causes of the disparities?
• 01:12:18Now you based on my understanding,
• 01:12:20you pointed out that if you control for
• 01:12:22income that you still see the disparity.
• 01:12:25But there was an interesting aspect of
• 01:12:27this question which is. For example,
• 01:12:29microbiome is influenced by environment,
• 01:12:30the diet, stress etc,
• 01:12:32and those who experience poverty
• 01:12:33are impacted tremendously.
• 01:12:34But if poverty caused by structural racism.
• 01:12:37Then we need to address racism as well.
• 01:12:39Question mark,
• 01:12:40but you're saying that poverty
• 01:12:42if you control for poverty you
• 01:12:44still see the difference.
• 01:12:45I am and this is. This is kind of a.
• 01:12:49A tricky question, and when we
• 01:12:52begin to see how everything is so.
• 01:12:54Intertwined and I guess that really
• 01:12:58what really what I'm saying is
• 01:13:01from where we stand right now.
• 01:13:04I wouldn't discount anything.
• 01:13:05I think that's really the message
• 01:13:08that I wanted to get across is.
• 01:13:13I yeah. I wouldn't discount anything.
• 01:13:18I think that that all of these
• 01:13:20approaches are legitimate possibilities.
• 01:13:22But to Opry Ori say no,
• 01:13:23it can't be one thing.
• 01:13:25It can only be the other thing I think is
• 01:13:27is a disservice is doing a disservice.
• 01:13:30Well, I appreciate.
• 01:13:31I appreciate that sentiment in
• 01:13:32particular. It may be 'cause I actually
• 01:13:34had written down some questions as we
• 01:13:36went along in the talk was so nice
• 01:13:39that as you went along you answered
• 01:13:40my questions and stuff, you know.
• 01:13:42But when I wanted to talk about
• 01:13:44one of my questions was is there
• 01:13:46actually a political price?
• 01:13:48For endorsing or not endorsing a potential
• 01:13:51genetic role in disparities and I,
• 01:13:55I think that you've kind of.
• 01:13:59Well, I'll ask,
• 01:13:59ask you to speak to that because I
• 01:14:02think that you imply that there are
• 01:14:04some people who feel stronger than
• 01:14:06we shouldn't go in that direction
• 01:14:08for all the reasons you talked about.
• 01:14:10And by the way,
• 01:14:11the history of eugenics in medicine
• 01:14:13is not a subtle one.
• 01:14:14In New Haven's role and major
• 01:14:16academic institutions all over,
• 01:14:17including Yale's role in eugenics in
• 01:14:19the earlier part of the 20th century.
• 01:14:21In we carry this legacy with
• 01:14:23us as physicians,
• 01:14:24unfortunately,
• 01:14:24and his academics so that that
• 01:14:26caution is certainly there.
• 01:14:27But your message seems to be.
• 01:14:29Let's keep every door open and let's
• 01:14:31look everywhere we can amass strikes me
• 01:14:34as as as as something that strikes me.
• 01:14:37Amerson, you concomitant,
• 01:14:38you seem less married to a specific answer
• 01:14:41then you are to solving the problem.
• 01:14:43I agree,
• 01:14:44I think that in my in my short career
• 01:14:47just reading and talking and networking
• 01:14:50and being exposed to all different ideas
• 01:14:53in many different contexts has I can.
• 01:14:56I can see how it shifted and
• 01:14:59refined my view. And so I I.
• 01:15:02I come to this question with thoughts
• 01:15:04about how I'd like to investigate it.
• 01:15:08An roads I'd like to go down,
• 01:15:11but there's so many twists and turns
• 01:15:13and it's so complex. That I think.
• 01:15:18Said saying at the outset,
• 01:15:19this is what it must be.
• 01:15:22An I reject everything else has the
• 01:15:24has the potential to actually further
• 01:15:27undermine and hurt the very people that
• 01:15:30you're trying to help by excluding
• 01:15:33them from potentially benefiting from
• 01:15:35something like I think about it in a
• 01:15:38similar way to the lack of inclusion
• 01:15:42of African American folks in clinical
• 01:15:44trials in vaccine trials like it.
• 01:15:47In my mind,
• 01:15:48it seems very clear that there was.
• 01:15:52Kind of a dual mistrusted
• 01:15:54the medical institution,
• 01:15:56but also maybe not wanting to two.
• 01:15:59Go out of one's way to bring in members
• 01:16:02from this group that has a history
• 01:16:05of being a manipulated by or taken
• 01:16:09advantage of by the medical establishment.
• 01:16:12They were not included and therefore
• 01:16:14did not have the opportunity to.
• 01:16:17Benefit from discoveries that
• 01:16:19may have been made.
• 01:16:20So I'm not saying that's what would happen,
• 01:16:23but that's that's my worry
• 01:16:25that if we say upfront,
• 01:16:27no,
• 01:16:27this can't be that you have denied the
• 01:16:30opportunity to benefit from something.
• 01:16:32If it turns out to be there.
• 01:16:36Thank you. Another question, please,
• 01:16:38are you aware of quality improvement
• 01:16:41initiatives or other interventions
• 01:16:42that have shown the ability to narrow
• 01:16:45the disparities in maternal neonate?
• 01:16:46Allowed comma and black women?
• 01:16:48Better access to care, etc.
• 01:16:50Are you aware of research that looks
• 01:16:52specifically at adverse childhood
• 01:16:54events and racial disparities in
• 01:16:56maternal neonatal outcomes? So two
• 01:16:58somewhat different questions,
• 01:16:59so I am aware of broadly research in
• 01:17:03both of those domains because it's.
• 01:17:05That's not the space that I work in as much.
• 01:17:09I haven't really been in.
• 01:17:12An exploring that literature recently.
• 01:17:14But there's certain there certainly
• 01:17:16is a robust literature about
• 01:17:18average early childhood experiences,
• 01:17:20aces, and how those experiences
• 01:17:22can drive disparities,
• 01:17:23and in terms of interventions.
• 01:17:26I come across them as I'm kind of
• 01:17:29looking for articles on other topics,
• 01:17:32so I know that certainly they do exist,
• 01:17:35and there have been some.
• 01:17:37Strides need an people are
• 01:17:39putting their work out there so
• 01:17:42you know that that does exist,
• 01:17:44but it hasn't been in kind of a.
• 01:17:48A sweeping manner that's been able to
• 01:17:53kind of infiltrate on a national scale.
• 01:17:58Practice patterns.
• 01:18:00Here's
• 01:18:01a provocative.
• 01:18:03Point that must be raised.
• 01:18:07Door we didn't open.
• 01:18:08We talked about leaving all the
• 01:18:10doors open to try and get to the
• 01:18:11answer to make things better.
• 01:18:13The door we didn't open was
• 01:18:15physician behavior in practice,
• 01:18:17and that's the one thing
• 01:18:18we can always control.
• 01:18:20We really perpetuated a lack
• 01:18:22of physician accountability.
• 01:18:24To a group of learning
• 01:18:25medical providers no less.
• 01:18:26That's the common on this thing,
• 01:18:28so a lack of position to kind of.
• 01:18:30I don't know if that's been perpetuate it,
• 01:18:33but I have to say I
• 01:18:35found this traumatizing.
• 01:18:36Do you want to comment on that?
• 01:18:40What was traumatizing, I'm sorry, well I get
• 01:18:42the sense from the from the from the
• 01:18:45question that that the concern here
• 01:18:47was that we didn't talk about physician
• 01:18:49accountability and that this is this is
• 01:18:51this has been raised but we didn't talk
• 01:18:54specifically about what there may be
• 01:18:56a physician's role in this disparity,
• 01:18:58because as I know you know well,
• 01:19:01amorous that there have been studies
• 01:19:03that show that even among those that
• 01:19:05are quite sure we're doing it right.
• 01:19:07In fact, we're not.
• 01:19:08Can not always everyone all the time,
• 01:19:11but in fact there are certainly disparities
• 01:19:13in the way we care for patients.
• 01:19:15Do you do you want to comment on
• 01:19:18how physician action activity may?
• 01:19:21Be impacting that disparity specifically
• 01:19:23in maternal and neonatal outcomes.
• 01:19:27So it is always a challenge because I think.
• 01:19:33In the. Nick, you it can feel like we have.
• 01:19:38More control over the immediate
• 01:19:41environment of the patient
• 01:19:42because they were there with us.
• 01:19:45And we don't. Necessarily recognize
• 01:19:50in ourselves when perhaps we are
• 01:19:55perpetuating some of the disparities.
• 01:19:58I guess I'm not really.
• 01:20:00I mean, it's it's true, it is.
• 01:20:02It is a huge.
• 01:20:07It is a topic that is right for
• 01:20:10discussion that needs to be discussed
• 01:20:12and should be incorporated.
• 01:20:13I will say I didn't really incorporate it
• 01:20:16into this conversation as much because I.
• 01:20:19I'm thinking more at the
• 01:20:23population level and it's very.
• 01:20:27If it's a challenging.
• 01:20:30It's a challenging realization to
• 01:20:33have that you may be perpetuate ING.
• 01:20:36Stereotypes in situations where.
• 01:20:42You're propagating disparities,
• 01:20:44but I'm not. I guess I don't really
• 01:20:48know what to say.
• 01:20:49I know I appreciate that Emerson.
• 01:20:51I appreciate that went through a lot
• 01:20:53of things and you didn't you didn't.
• 01:20:55You didn't in this talk at the cover,
• 01:20:58every possible aspect of this,
• 01:20:59but there was an awful lot
• 01:21:01of things that were covered,
• 01:21:03but certainly our role as physicians,
• 01:21:04our complicity as physicians,
• 01:21:06and perhaps contributing to those
• 01:21:08disparities are something we need to look at.
• 01:21:10And this is where again,
• 01:21:11I think the comparison to other
• 01:21:13countries where perhaps the racism is.
• 01:21:15And other settings where racism is different,
• 01:21:17perhaps less, perhaps more.
• 01:21:18How all these things could compare
• 01:21:20to see to see how we do this.
• 01:21:22Again, I think the ultimate goal,
• 01:21:24and I appreciate the sentiment
• 01:21:25you're trying to do is to try and
• 01:21:28find out what's causing the problem
• 01:21:29so that you can make it better.
• 01:21:31You and a lot of other smart
• 01:21:33people trying to sort this out,
• 01:21:35and no doubt I shouldn't say no doubt.
• 01:21:38I think most of us would agree that
• 01:21:40physician behavior is certainly
• 01:21:41part of the problem.
• 01:21:42And this is something that we
• 01:21:44have to keep our eyes open to
• 01:21:46another question please,
• 01:21:48I'm wondering if you can comment on the
• 01:21:50relationship between low birth weight,
• 01:21:52preterm birth and racism,
• 01:21:53i.e.
• 01:21:54Through mechanisms like increased cortisol,
• 01:21:55are there studies that have looked at
• 01:21:58perceived racism and how that itself
• 01:22:00is associated with low birth weight?
• 01:22:03So there are studies that have looked at
• 01:22:06that the results are somewhat conflicting.
• 01:22:10Ann are not the most robust.
• 01:22:14I think some of the more
• 01:22:18interesting studies have looked at.
• 01:22:21Have looked at women who underwent.
• 01:22:23I'd like a an acute stressor during
• 01:22:26the pregnancy and then followed them
• 01:22:29to see what happened with their
• 01:22:32babies and there was an increased.
• 01:22:35Risk or rate of very low birth weight.
• 01:22:38I'm thinking specifically about
• 01:22:40kind of a cross sectional study that
• 01:22:43was done in Iowa before an after.
• 01:22:46I believe it was an ice raid for to look
• 01:22:49for illegal immigrants and deport them,
• 01:22:53and they looked at.
• 01:22:55They looked at the at the.
• 01:22:58Rate of low birth weight,
• 01:23:00kind of in the year before that
• 01:23:02happened and then in the nine
• 01:23:04months to a year after that happened
• 01:23:07in compared between the two.
• 01:23:09But in terms of in terms of.
• 01:23:14That that relationship with.
• 01:23:17With how with experienced racism,
• 01:23:20it's it's often self report.
• 01:23:22I just have I think that we that
• 01:23:24we are still struggling to find a
• 01:23:27good measurement measurement tool
• 01:23:30that's more accurate and reliable.
• 01:23:32But the court,
• 01:23:34like the correlation doesn't
• 01:23:36is not that robust.
• 01:23:38From the few studies I've seen.
• 01:23:41There are
• 01:23:41a couple other questions which
• 01:23:42are interesting which I'm not
• 01:23:44going to have time to get to,
• 01:23:45but I'm going to encourage the people
• 01:23:47who ask him one related to the potential
• 01:23:48role of doulas in reducing stress is
• 01:23:50another about policy actions that you
• 01:23:52might recommend so I would I would
• 01:23:53ask those individuals if you send
• 01:23:55something to me through that website.
• 01:23:56I mentioned to biomedical ethics at Yale,
• 01:23:58I'm if you reach out to that
• 01:24:00to Karen who's our manager.
• 01:24:01I'll see that these questions get
• 01:24:03to Doctor Kaiser and if you have
• 01:24:04a minute or two to think about
• 01:24:06it to respond to an email.
• 01:24:07If you want amorous but I knew I
• 01:24:09wouldn't be able to get everything and
• 01:24:11now we only have a minute or two left.
• 01:24:13But I want to leave it with a
• 01:24:15chance for you to share with us.
• 01:24:17Any final thoughts you have any
• 01:24:19suggestions you have about the
• 01:24:22direction this work should go?
• 01:24:24I want you to just.
• 01:24:25We've got just a minute or two left.
• 01:24:27I want you to have the final word on
• 01:24:28this on whatever topic you want to.
• 01:24:30However you want to address the topic.
• 01:24:32I think it's a.
• 01:24:34It's a hard topic there.
• 01:24:37Challenging conversations to have.
• 01:24:38It's really exciting because
• 01:24:40of the opportunity to work in,
• 01:24:43uh, in multidisciplinary teams.
• 01:24:45This problem. This issue is so complex.
• 01:24:48It's so multi layered everything is
• 01:24:51so entangled that you really need.
• 01:24:54Awareness of the research and the
• 01:24:58ideas that are being discussed in
• 01:25:02other realms outside of the hospital.
• 01:25:06That that will enrich the work,
• 01:25:08but I guess what I'm left with
• 01:25:11is the importance,
• 01:25:12the necessity of working in teams
• 01:25:14so that you can amass the team.
• 01:25:16That's going to have the expertise
• 01:25:18to be able to delve into all of
• 01:25:21these different realms and begin
• 01:25:23to make sense of all of it,
• 01:25:25and to make sense of how it fits together
• 01:25:28so that we understand where we go next.
• 01:25:32Thank
• 01:25:33you very much Doctor,
• 01:25:34Amorous casual this has been an
• 01:25:36extraordinary 90 minutes and we're
• 01:25:38very grateful for your time and your
• 01:25:40expertise and we look forward to your
• 01:25:42next visit in person back home to Yale.
• 01:25:45Thank you all very much for attending an.
• 01:25:48We're getting nice comments
• 01:25:49here from folks who very much
• 01:25:51appreciate the talk amorous I owe
• 01:25:53you 1 this was terrific. Thank you
• 01:25:56so much. Goodnight folks. Here.