Identifying Cognitive Difficulty among Middle Eastern and North African (MENA) Americans

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In this episode, Matt and Lauren speak with Dr. Tiffany Kindratt whose research focuses on examining health outcomes among the Middle Eastern and North African (MENA) population, a group that was – until recently – categorized as “white” by the US government despite. Evidence showing their health and lived experiences are different. We’ll get into a recent American Journal of Public Health article authored by Dr. Kindratt that that examines how cognitive difficulties differ among the MENA population when compared with other racial and ethnic categories.   

More resources

Faculty Profile: Tiffany Kindratt, PhD, MPH 

Health Survey Research (HSR) Lab @ University of Texas at Arlington 

American Community Survey (ACS)  

AJPH Article:   

Kindratt TB, Smith A. Cognitive Difficulty in Middle Eastern and North African Adults Living in the United States Compared With Other Racial and Ethnic Categories, 2017-2021. Am J Public Health. 2024 Nov;114(11):1265-1274. doi: 10.2105/AJPH.2024.307803. PMID: 39357001; PMCID: PMC11447784. 

Transcript

Matt Davis:

When examining health outcomes, researchers categorize race and ethnicity into groups. That often entails combining smaller subgroups, sometimes just to simply increase sample size. Probably the most common approach is separating the population into non-Hispanic white, non-Hispanic Black, Latino, and I'm putting this in air quotes, even though you can't see it, "other." It's come to light though in recent years, that the aggregation of race and ethnicity into these larger groups can sometimes mask important differences.

In this episode, we'll discuss a recent article that examined how cognitive difficulties differ among Middle Eastern and North African Americans. I'm Matt Davis.

Lauren Gerlach:

I'm Lauren Gerlach.

Matt Davis:

And you're listening to Minding Memory.

We're joined today by Dr. Tiffany Kindratt. Dr. Kindratt is an Assistant Professor in the Public Health Program Department of Kinesiology, and the College of Nursing and Health Innovation at the University of Texas at Arlington. Her research focuses on examining health outcomes among the Middle Eastern and North African population, sometimes abbreviated as MENA, who until recently were defined as white by the US government, despite evidence showing their health and lived experiences are different. She's here today to speak with us about her recent study.

Tiffany, welcome to the podcast and congrats on your recent paper.

Tiffany Kindratt:

Thank you. I'm very happy to be here. I was very excited to have my first publication in the American Journal of Public Health as an epidemiologist. That's the biggest, I feel like, accomplishment that I've had so far.

Matt Davis:

And we'll jump in here to questions in a second, but your student was a co-author too, right? Got to work with you on it.

Tiffany Kindratt:

Yes, yes. I had an amazing student, Alexandra Smith, and she was actually an MS in exercise science student, and she took a class that I taught on teaching them SAS using national health data, and then she worked with me afterwards and it was just a wonderful experience with her, so it was very exciting.

Matt Davis:

That's a lot of fun, and what a valuable experience for her to go through that process with you. Dr. Kindratt was the lead author of a study titled, Cognitive Difficulty in Middle Eastern and North African Adults Living in the United States Compared With Other Racial and Ethnic Categories, which was published in the American Journal of Public Health. A link to the article can be found attached to this episode, make sure to check it out.

So to start things off, your article discusses recent policy changes regarding the identification of the MENA population in federal data. I was wondering if you could tell us a little about that policy change?

Tiffany Kindratt:

Sure. So just to give a little bit of background on that before going to this specific change. So, the US has been categorizing people by different places of origin or race and ethnicity since at least like the early 1900s. And it really became formalized in 1977 by the Office of Management and Budget. They came out with a policy called Statistical Policy of Directive 15, or SPD 15, and this is where they stated that all of the different organizations, anyone receiving federal funding had to have these specific minimum reporting categories. And so with that, they use that to allocate billions of dollars for different resources throughout the US, from education, to health research, to many others.

And so it has not changed a whole lot since then. There were some small changes from 1977 to 1997, which has been what has been in effect until recently. And so those included two questions. So the first question was a separation between ethnicity. So whether or not someone was Hispanic, Latino, or of Spanish origin, or not. That was its own separate question. And then there were specific groups for race. So white, meaning any person of European ancestry, Middle Eastern, or North African. Black or African-American, Asian, American Indian, Alaskan Native, native Hawaiian or Pacific Islander, I believe I have them all. And so because of that, in 1997 being the last time it had changed, around 2015, they started to look at making new changes. So getting close to that 20-year mark of changing the different categories, and nothing really happened at that time.

And so in June 2022, Dr. Karin Orvis, who's the Statistical Policy Directive, or she's actually the Chief Statistician of the United States, and led this effort and came out and said, "Okay, well based on the changing demographics, it's time to look at this and see if there needs to be a change.” So in September 2022, the Office of Management and Budget started holding listening sessions. They had a formal review group, and they were able to receive feedback from the public on many different types of changes. And then they came out with some proposed changes in January of 2023, and one of those changes being adding MENA, or Middle Eastern and North African individuals, as a separate checkbox from white. So as I said before, they were part of that definition of the white race group. And then in May, or then in March 2024, the Office of Management and Budget came out with the new guidelines for race and ethnicity.

And so to go over the changes, there really are four main changes that took place. So the first one was to combine race and ethnicity into one question. So instead of having that separate Hispanic, Latino ethnicity question, it will now be part of just one question. The second is to add the Middle Eastern and North African, or MENA group, as a minimum category. So they were previously grouped with the white race group, which also includes people of European ancestry. So there are now these seven categories of American Indian Alaska Native, Asian, Black or African-American, Hispanic or Latino, Middle Eastern or North African, and then Hawaiian or Pacific Islander, and White.

The third change was to require the collection of detailed race and ethnicity categories as a default. So not only is there this small checkbox for them to say, "Oh, I'm MENA descent or Hispanic descent," there are also different checkboxes underneath that that represent the largest populations within that larger group. And then there's also a place where people can write in responses. And then the final changes that they made were updates to the terminology. So they removed things that were considered offensive, like far East. They removed other, in front of Pacific Islander, and they made some minor details to the last guidelines, which included things like Cuban, which was listed in there twice.

Matt Davis:

So you're probably a good person to ask because I know you have experience with a lot of different national sources of health data, things like NHANES and MEPS. Are you seeing all these variables show up correctly across the different sources that you've worked with?

Tiffany Kindratt:

So, the change was in March 2024, but they do not have to actually change it until March of 2029.

Matt Davis:

Interesting.

Tiffany Kindratt:

So the guidelines came out, they have until September of 2025 to present how they're going to make the change, and then they have until March of 2029 to make it. Now, the first official word that I've heard of the change is through the US Census Bureau and the American Community Survey. They are going to change it in the 2027 American Community Survey. It will have the new categories, and then it will be released for fall of 2028.

I had a discussion with someone from the AHRQ, Agency for Healthcare Research and Quality, and they are hoping to implement it soon, but some of the discussions were focused on concerns about small sample size, whether or not people will actually check that box, and whether or not that will have to remain restricted for a little bit of time.

Matt Davis:

As a person that does work in this area, you must have these things marked on your calendar as potential times that you could access, yeah.

Tiffany Kindratt:

I know. I sent my first meeting invite for September 1st of 2028 to a colleague of “will we have ACS data for MENA?” And so yeah, yeah, it's an interesting time.

Lauren Gerlach:

I was hoping you could tell us a little bit, what underpins the decision to combine these geographic regions, thinking about Middle Eastern and North African kind of areas?

Tiffany Kindratt:

Yeah, that's a great question. And this population is often defined somewhat differently, and I don't think that there's any one specific approach that is standard that one person wants. I would say that they've sort of looked at it in two different ways. The idea is to look at it as a geographically created category or as an ethnic category. And so looking at it as a geographic category, putting Middle East and North Africa is more inclusive and includes both Arab and non-Arab countries that have similar cultural and linguistic backgrounds, but may not all necessarily be of the Arab League. Versus the ethnic category, which would be considered more Arab versus non-Arab.

And so I think in research studies, sometimes people do define it a little bit differently. When I did a different study, I had multiple different students and we were looking at the comments. So when I mentioned before in January 2023, they came out with this comment period to allow people to say what they wanted to about these new changes. Well, I thought it would be a great idea for students to just look at the comments and compile them and let's see if they approve or disapprove of this. At that time, I didn't realize there'd be over 20,000 of them, and so we were able to look at over 6,000 of them. And some of the categories were... well, some of the comments were on things like Armenia, and people wanted Armenia to be part of the MENA category, whereas others may not consider that. And so it's partly due to self-identification, but yeah, I think the idea was to make it the most inclusive.

Matt Davis:

So, many of us have some experience with the American Community Survey. I personally did not realize that it has measures of disability. Can you tell us about those measures?

Tiffany Kindratt:

So there are actually six questions on disability in the American Community Survey, and these questions have been on there since 2008. They cover hearing difficulty, vision difficulty, cognitive difficulty, which was used in this study, ambulatory difficulty, self-care difficulty, and independent living difficulty. They're all yes or no questions, and so questions would be something like, so say for ambulatory difficulty, it would say something like, "Does this person have serious difficulty walking or climbing stairs?" For independent living difficulty, it said something like, "Because of a physical, mental or emotional problem, having difficulty doing errands alone, such as visiting a doctor's office or shopping." And then the respondent or their proxy would answer yes or no to that.

What's interesting about this is that there was actually a proposal to change this, and I believe it came out last year and they proposed to change it to these six questions from the Washington Group Short Set on Functioning, and that had similar questions but it made them on a scale, which ranged from “no difficulty” to “cannot do it at all”. And it actually would have reduced the percentage of disability in the US, and so during the comment period for that change, there was a lot of hesitation by the disability community and it did not go through. It did not.

Matt Davis:

It's very good to know. I think of the ACS mostly as a place to go for denominators estimates, never numerator estimates. So this is very cool.

Lauren Gerlach:

So for your study, you utilized something called the American Community Survey. I was hoping you could tell us a little bit about this resource and what types of information the survey contains.

Tiffany Kindratt:

Yeah, so the survey really started in the early 2000s, and it took the place of the long form census. So after 2000, they changed the census that is every 10 years to be very basic, with just basic information about every individual in the household. And so then the ACS is sent out to a sample of households every year to sort of fill in those gaps. And so it doesn't have a lot of health related information, it only has those disability questions. But then it also has a lot of information about employment. It has ancestry information, it has place of birth. It also has different county level information that can be used for combining with other studies when needing population sizes. And it's a really good resource to be used for other things.

Lauren Gerlach:

We understand for your study, you were looking at a primary measure to identify cognitive issues from the American Community Survey. Could you tell us a little bit about how that was captured and what was asked of respondents?

Tiffany Kindratt:

Yeah, absolutely. So for this study, we used a measure of cognitive difficulty, and it was one of the questions that was part of the six disability questions that are measured through the ACS. So the question was, “because of a physical, mental, or emotional problem, did an individual have difficulty remembering, concentrating or making decisions?” And that was a yes or no response question.

Matt Davis:

So I'm curious, what was your justification to examine the association between MENA status and cognitive difficulty separately by state?

Tiffany Kindratt:

That is a great question. And so to answer that question, I really have to put my research in context too. So me working on this study, as well as many other studies on the MENA population, I have started working on research since really about 2011. Really being interested in why this population was considered part of the white race group. I was at the time, just a recent MPH graduate and had really only learned about it a little bit through my mentor.

And I actually filled out a census in 2010 here as an adult for the first time, and so it was very easy for me. I was non-Hispanic, I was able to fill out, at the time it had white, black, and then it had the different checkboxes, but it didn't have either a Middle Eastern or North African or Arab checkbox. And so it was kind of interesting because I had heard of it before. And then I lived in England, and when I was in England, they had a checkbox for the Arab population and many of these other populations. And so I was always kind of really fascinated why this group didn't have it. At the time, I was also working at medical schools and training providers and so it was kind of like this side research that I was able to do.

And so when I became a faculty member in 2019 and was able to really start doing my own research, it was like, okay, well what evidence is missing and how can we make this happen? Part of it was looking at older adults and some of the studies that have been done in particular states like California and Michigan, really have started to show the differences in that the Arab or MENA population were having a higher prevalence of cognitive limitations, but they were smaller studies. And so I applied to do this study through CAPRA at the University of Michigan in December of 2022. And so this was right before the comment period came out with the proposals to add MENA as a checkbox.

And so part of the decision was really, the fact that number one, there are no studies that have any estimates by state. They're mostly either done community-based within the states, or done on a national level but probably don't have MENA in the category. And so it's really only been limited to either foreign-born Middle Eastern, North African individuals in the National Health interview survey, or the ACS. Also, me being in Texas and being in a place where I've met more and more people who have said, "Oh, I'm of Middle Eastern, North African ancestry," learning of a lot of different migration from different states wanting to raise that evidence. I think when I did my initial literature search, there was maybe one study that had been published on the Arab or MENA population in Texas, and so just trying to add that into the mix there.

Lauren Gerlach:

Terrific. So I was hoping you could walk us through your study and tell us a little bit about what you found and if there was anything that surprised you.

Tiffany Kindratt:

Sure, yeah. So this study included the data from the American Community Survey from 2017 to 2021. And so the way that the American Community Survey is set up is when it provides five-year estimates, then it's more similar to what the actual population size would be across that five-year period. And so when the study was first designed, it was partly due to the fact that there weren't those state estimates before, and also previous studies tended to look at the comparisons with white only, because of them having that definition as part of the white race group. So in my head I'm thinking, okay, well how else can we move this forward? One possibility is to compare them to all of the other racial and ethnic groups to see if we can justify that there's a disparity. Not to say it's better or worse, it's just to show that there is a difference and that they should not just be compared to white and move the research forward.

So we used 2017 to 2021 data and looked at age 45 and older to include that middle age group to show that there is the cognitive difficulties that can emerge younger. And then we just looked at all of the different racial and ethnic groups that were part of those new proposed categories. And then we did an age and sex adjusted prevalence of those, and then looked at odds ratios and adjusted for some of the different factors that they had in the ACS data set. So there's nothing really related to health that I was able to include in that, but things like education, nativity status, age, sex, etc. And so some of the main findings were really that we found that on the national level, MENA adults had higher odds of cognitive difficulty compared to all of the other racial and ethnic groups, except for the non-Hispanic, native Hawaiian, and Pacific Islander group.

And then we found some different patterns across the different states. So when we looked at age and sex-adjusted prevalence, the highest was in Michigan at 8.3%, then California was 6.96%, New York was 3.96%, and Texas was 4.44%. And I'll just mention the different states here. So when I actually did the study, I tried to find the top states and I looked at population sizes beforehand of the entire population, and then picked the top four. So California having the largest, New York having the second largest, Michigan having the third largest, and Texas having the fourth largest, that would be by actual population size. When you look at the percentage, Michigan had the highest percent at 2.7% there.

And so there were different nuances when we looked at the different odds ratios there. One of the surprising things was that the pattern kind of differed for all the different racial and ethnic groups except for the Asian group. So MENA had higher odds of cognitive difficulty across all the different states than the Asian subgroup. And so I don't know the exact reason why for that, but it kind of makes me think of that definition of the geographic group versus an ethnic group. And maybe that has something to do with it.

Matt Davis:

It's probably hard to know from a causal mechanism and everything, but I guess, what are your thoughts on why? Why do they have higher cognitive issues?

Tiffany Kindratt:

Yeah, so it's really interesting, just when trying to think about that as just thinking about many of the different factors that contribute to health and that have contributed to differences in their health outcome. When you look at modifiable risk factors for dementia, for Alzheimer's, and you look at this population, you look at the different institutional and interpersonal discrimination as this population experiences. It could be if there is a group in this certain state, there is differences that certain states have higher percentages of immigrant populations. And so if they're coming from different war-torn countries, also the discrimination coming from different government policies, travel bans, etc, that has contributed to that, and just the different perceptions of themselves and others.

Lauren Gerlach:

So researchers, depending on data, often have options with how to classify race and ethnicity. And we know that there can be important limitations and biases that can come with those categorizations, but it can be an important lens to be able to view disparities and equities and racism. As you, as someone who's really embedded in this work, can you offer any key takeaways for folks to think about in these limitations and in thinking about designing studies that look across different racial and ethnic groups?

Tiffany Kindratt:

Yeah, absolutely. So, I think when there is self-identification data, then that is always best, if you are not having to create this actual group. So for this study, we used ancestry data in place of birth data from the American Community Survey. And that group, anyone that was part of these 25 first or second ancestries reported, or 21 countries of birth, or these additional countries or transnational communities that were not available as part of the ACS, they were categorized as MENA. Now, that person may have selected MENA and may have also selected white, or may have just selected white, or may have selected other. And so if available whenever possible, it's always better to use the self-reported data of how someone identifies.

Also when available too, to not just look at populations like this as a homogenous population, that there is such large heterogeneity within the group. And so when you are able to disaggregate that and look at large populations for MENA, the Lebanese population may be very different from the Somali population. And that is also, some of those differences may have occurred across the different states. There's much different populations, say Minnesota may have more Somali population versus Michigan, which may have more Iraq, Chaldean, and Lebanese. And so there's all these differences there that if you can break it down and go into those smaller groups without having to make a bigger sample size and still have enough power, then that's definitely best.

Matt Davis:

I don't know if this is a perfect analogy, but I'll take a shot at it. It reminds me of when I work with students and a question comes up for a geographic analysis. They're like, "What's the correct level of geography when things nest?" And my answer usually is, "Well, what level is the variation at?" And it feels like, I mean, it's definitely more complicated here because you're dealing with personal identity and a lot of things, but how fine do you go? And I don't know, is that a bad analogy to think of in terms of where the variability is across the groups?

Tiffany Kindratt:

Yeah, no, I think that's great and I just feel like it's always gray and it's always, well, it depends, and it just kind of... What's the question? What's the goal? With this study, it was not to mass those differences in this group. This study was meant to build on the existing evidence because there hadn't been anything really that was done comparing MENA as part of those specific groups. And so it was not meant to sort of overshadow or overlook that heterogeneity, it was really just meant to be like, hey, please give this population a category so that they can have resources and they've not been able to be identified for decades.

Matt Davis:

So I'm reflecting on the little bit of literature I know in this space, and I was just curious. I've seen some studies that looked at sort of length of time spent in the United States, and I'm just curious, are you thinking about or do you think that would matter in terms of for this population, the amount of time they've been in the United States in terms of the impact of the association between, with cognitive outcomes?

Tiffany Kindratt:

Yeah, I think looking at also the other literature as well and seeing that it definitely is possible to have an impact on that, I definitely think that. Also the age at migration, migration period. So there's been some previous work that we've done before and we've looked at these specific time points of migration and before certain elections, before 9/11, and that can really impact it as well. And also, other potentially modifiable risk factors.

Matt Davis:

So regarding this line of work, what's next for your team?

Tiffany Kindratt:

Oh, that's such a great question. It was so funny when it actually was approved in March, first of all, I was so shocked. I was like, what? And my research is small compared to so many others that have done work. And so then it was just kind of like, well, what am I supposed to do now? And so, yeah, so there's a lot of things that we've been trying to do to expand this and look at some other things.

I mentioned before briefly that I used to work at a medical center, and so part of my other lines of work are really looking at patient and caregiving experiences, and patient-centered care, and sort of starting to look at that within this population and try to find that. I'm also trying to look at things related to expenditures and how we can link different data sources. The ACS, I recently found out can be linked to the HINTS, so the Health Information National Trends Survey. And trying to figure out how we can look at different disparities there, not only for the MENA population, but just for cognitive health and health across the life course in general.

I also have a bunch of students that want to come in and do things, and so looking at things like, okay, well, how do we get research funding and how do we really advocate for this with the National Institute for Minority Health Disparities? And looking at, okay, how many studies actually have actually been funded for this population? What is in the NIH reporter and how can we make sure now that they are recognized as a minority category, they're listed on the NIMHD's website as a priority population, but yet they haven't been in those funding announcements yet. And so as things evolve, how do we get that advocating done there?

Lauren Gerlach:

Is there anything else we haven't covered that you want listeners to know?

Tiffany Kindratt:

No, I think that's really it. I would just say that if anyone's interested in this topic and linking datasets and collaborating, finding innovative ways to look at this, I'm definitely up for collaboration.

Matt Davis:

Tiffany, thanks so much for joining us today.

Tiffany Kindratt:

Thank you, it was great to be here.

Matt Davis:

If you enjoyed our discussion today, please consider subscribing to our podcast. Other episodes can be found on Apple Podcasts, Spotify, and SoundCloud, as well as directly from us at capra.med.umich.edu, where a full transcript of this episode is also available. On our website you'll also find links to other resources we've created specifically for dementia research.

Music and engineering for this podcast was provided by Dan Langa. More information is available at www.danlanga.com. Minding Memory is part of the Michigan Medicine Podcast Network. Find more shows at michiganmedicine.org/podcasts. Support for this podcast comes from the National Institute on Aging at the National Institutes of Health, as well as the Institute for Healthcare Policy and Innovation at the University of Michigan. The views expressed in this podcast do not necessarily represent the views of the NIH or the University of Michigan. Thanks for joining us, and we'll be back soon.