Origins of the Health Disparities Narrative

I recently did a guest lecture at Berkeley where the students asked me two questions that left me scratching my head...
1) When did the 'health disparities narrative' become dominant in public health, and 2) What dominant narratives about the health of socially-marginalized racial groups preceded it?
I don't know. But those are intriguing questions that deserve answers, so I'll ask for your indulgence as I flail around with some possible answers.

Defining the 'Health Disparities Narrative'
In public health, we tend to think about minority health in terms of 'health disparities'.
When we see that the health of a minority group is worse than that of socially-dominant groups, that is expected based on our narrative of how minority groups fit into social structures, and how these social structures influence health.
When we encounter exceptions to that general rule (cases that don't fit the narrative of health disparity) we tend to doubt the data and dismiss the findings. In those cases where the data shouts out over our attempts to silence it, we call it a 'paradox'.
So that's what I mean by the 'health disparities narrative' - an overarching narrative structure that strongly influences what we intuitively believe or doubt about the health of socially-marginalized groups. Which stories are 'easy' to tell, and which leave us tongue-tied and confused?

From the 'Sign of the Gene'...
I was first introduced to epidemiology in the mid-1980's. My recollection is that the go-to explanation for health differences between racial groups was that 'race' described biological distinction - that the environments of the various continents had 'bred' races of humans with differential susceptibility to disease. This go-to explanation was so ingrained that it was rarely stated explicitly. Implicitly, one message was that if racial difference reflects biologic difference, then an observed health disparity reflects something 'natural'. A racial disparity could be considered a 'risk factor', and be the basis for 'raising awareness', but would have little application in primary prevention (one would not 'prevent' someone from being one race or another).
The classic example of this was sickle cell anemia, usually quickly followed by cystic fibrosis, to demonstrate that every race had it's unfortunate susceptibilities.

In the early-mid 1990's, running up to the sequencing of 'the' human genome, news stories hit hot and heavy linking any and all manner of diseases and even personality traits to genes. Almost all of these reports were not confirmed in replication studies, but one thing became increasingly clear: the genes that were implicated in diseases were never the same genes that had different racial distributions. And in that handful of cases where there was some overlap, like in HLA markers, nothing panned out in further study in a way that explained racial disparities in health.

...and racism...
Despite the complete lack of evidence for the genetic basis of disparate health outcomes, genetic origins continued to be (and continues to be) the go-to explanation for many people in medicine and public health.

Fortunately, I was taught epidemiology by Sally Zierler, who countered the 'biologic distinction' interpretation of observed racial disparities, and offered instead the interpretation that racial disparities in health could be attributed to the relative social standing of those groups. Implicit in that interpretation was that a racial disparity should not be seen as 'natural': it should shock the conscience. It also leads to very different prevention strategies. Racism itself should be the focus, and Sally got a lot of heat for promoting that viewpoint.
A terrific example of this way of thinking is the ground-breaking analysis in 1997 by James Collins and Richard David, who pit the assumption of genetic origins head-to-head against an alternative hypothesis: that something about living as Black in America, especially during childhood, was the cause of high rates of premature deliveries seen among African-American mothers.

...to 'health disparities'...
The early 2000's is when I'd say, based only on my gut, that the way we think of 'health disparities' today really blossomed. I'm going to try to do a historical word count type of analysis to check that gut assumption, but in the meantime, I think it's safe to assert that the dominant interpretation of 'health disparities' as reflecting social structure is a recent phenomenon.
The prevention lessons we draw from the 'health disparity' narrative today are pretty varied - access to care, cultural competency, and also the 'fundamental cause' people like me - racism itself, the rest is downstream of that...

Epidemiologic Transition
The epidemiologic transition refers to the shift in patterns of causes of death, from chiefly infectious diseases striking all ages (and especially those under 5 years old) to chronic diseases that are more restricted to older populations. Epidemiology itself also had a few major transitions, but a little out of sync with the shift in mortality patterns. After 60 years or so of social epidemiology, infectious disease epidemiology rose in stature in the early 20th century. Infectious diseases dropped dramatically during both phases, but once the shift to chronic diseases as the major killers was largely complete in the 1950's and 60's, a new epidemiology arose, a chronic disease epidemiology which stressed multiple risk factors rather than single bugs. So, I suspect that the transition to chronic disease epidemiology was not linked to the development of the health disparities narrative, but it was a pre-condition.

Civil Rights Movement
I think the civil rights movement probably played a big role in the development of the health disparities narrative, but not as directly as one might at first think. Landmark legislation in the mid-1960's led to the involvement of the courts in race relations by the 1970's in a new way. Rather than being limited to assessing discrimination in individual cases, a new statistical reasoning made it's way into legal wranglings and regulatory frameworks: between affirmative action and desegregation orders, the quantification of inequity became a paramount consideration. My hunch is that these routinely quantified comparisons of racial groups played a big role in the development of the health disparities narrative. If one conceives of racial groups as being separate biological groups subject to evolutionary forces, then comparing racial groups to one another is like comparing apples to oranges - or really Granny Smiths to Cortlands. There are circumstances where comparisons make sense, but there is an assumption of difference built-in from the beginning. So I think the quantification of racial difference that the civil rights era ushered in certainly played a role, but other factors had to come into play as well.

Office of Management and Budget Standards for Data on Race and Ethnicity
As various Federal agencies struggled to enact regulations and enforce them, the fact that there is no agreed-upon definition of racial categories became clear. Rather than acknowledge that race is a complex characteristic, composed of many dimensions including self-identity and perception by others, the Federal Government tried to create a standardized set of categories that would be shared for all administrative purposes, with the Office of Management and Budget Directive #15 in 1977.
That may seem like an obscure bureaucratic detail, but the reason I connect it to the rise of the health disparities narrative is that by requiring governmental agencies to use the same five categories to describe race, data from multiple sources became comparable in a way that they had not been before. Death records could be matched to Census data (or at least appeared to be comparable), so race-specific rates were easier to calculate.
The use of these standardized categories was diffused throughout the government, and in particular required for research grants, including medical and public health research grants. As a result, not only was it possible to use comparable racial groups for comparisons, but the requirement that racial breakdowns be reported back to granting agencies implied an importance attached to race that encouraged researchers to analyze their results using racial categories as well. Steven Epstein has written a lot about that whole process.

Healthy People 2010
When I showed the charts below to Rachel, she made a great observation: that the rapid rise in the term 'health disparity' after 2000 is probably linked closely to the release of the Healthy People 2010 document, which had the secondary goal of 'eliminating health disparities'. Why did they use that phrase? When did they start using it? I've tried to find the exact date that this phrase entered the Healthy People documentation, but it'll take more research to nail that down.

In sum...
I suspect that the main shift in interpreting racial disparities in health has been from revealing inherent racial differences in biology to mirroring social structure. I'm not sure exactly when this happened, but my gut tells me that this shift happened in public health mostly in the late 1990's, early 2000's - certainly there were vanguards who foreshadowed this shift much earlier, and just as certainly there are laggards who have yet to embrace it. I'll be curious to see what text searching through publication databases reveals...

addendum: here is a quick & dirty analysis - the proportion of articles indexed in WebOfScience.com with 'racial difference', 'racial disparity', or 'health disparity' in the topics field. "Racial difference" (in purple) rises from 1991 2003, then plateaus or even drops in frequency. 'Racial disparity'(in green) was at low levels before 2001, then rises exponentially. 'Health disparity' (red) was virtually non-existent in articles published before 2000, then rises even more rapidly than 'racial disparity' as a topic term.


Addendum2: Another quick analysis of word counts in PubMed (which goes further back in time) shows Identical patterns (unfortunately, I swapped the green and red in these two charts). It is interesting to note that there was a jump in articles using the phrase 'racial difference' in the mid-1970's, and potentially a second jump in the mid-1980's

Health Disparities: Getting Worse or Getting Better?

Yes. Both. Simultaneously. With the exact same data.

For my general rip on health disparities research, see the previous (lower) post.

So the other day, I heard someone say that in almost all cases, (racial) health disparities are getting worse, not better. Which, of course fits perfectly with the scare tactics that much of public health relies on these days. I think when we public health types hear that, we think it means we need more resources to address health disparities.

But in the back of your head, doesn't it also say: all the work that's been done on reducing health disparities has been an abject failure, nothing we do works, and it's disheartening to contemplate moving forward? Wouldn't it be an even more powerful motivator to garner resources to be able to say "Hey, look at this, things are getting better". If you were a funder, wouldn't you rather build on success?

But the numbers are the numbers, right?

Actually... depending on how you look at the numbers, whether things are getting better or worse is all a matter of perspective.

Arguably, the most important health indicator of them all is mortality.

So, I went to one of my favorite websites, wonder.cdc.gov, and looked up trends in mortality by race and ethnicity over the past few years, and then threw it into a graph.

When I look at that graph, there are a couple things that jump out - first that there are rather enormous disparities in mortality by race in the US. Second that Hispanics and Asian/Pacific Islanders have much lower mortality rates than Whites. (How often do you hear about that?) And third, death rates for all racial/ethnic groups are declining fairly rapidly.

It isn't immediately obvious from this graph whether the racial disparities are getting wider or narrower, the differences between these lines looks pretty similar over this 9 year period.

So, let's look at the disparity using the official method.

You pick the healthiest group, then divide the other racial/ethnic groups by that group to get the relative disparity. In this case, the healthiest group is the Asians and Pacific Islanders, so you get this graph:

It's pretty clear that relative to Asians and Pacific Islanders, the disparity is essentially unchanged for Hispanics, and has increased for Whites and Blacks.

But I find this way of looking at things strange.

It obscures the fact that Whites are the dominant group in the US, so I did the same analysis, but using Whites as the reference group.

When you hear the term "racial disparity", what is the reference group that springs to mind?

At any rate, this picture is a bit different. The Black:White relative disparity in mortality is actually declining slowly over time, while the relative health advantage of Hispanics and also Asians and Pacific Islanders is increasing over time.

But the interpretation of whether

health disparities are getting better or worse over time depends on something besides which racial group represents your baseline - it also matters whether you divide (the standard method) or subtract.

When you plot the difference between Asian and Pacific Islanders rather than the relative disparity, you actually get a different interpretation:

that the difference between Asians and Whites has not been changing much over time, but the disparity between Blacks and Asians has been improving, the exact opposite conclusion one would reach from looking at the relative disparity.

And when you use Whites as the reference group for the difference, these results are pretty similar:

The Black:White disparity is clearly diminishing over time, the health advantage of Hispanics has been increasing slowly, and there is no apparent change in the health advantage of Asians.

I don't want to bore you with the math that explains all this, but I guarantee I haven't done anything funny. It's just that when you subtract, most health disparities appear to be on the decline, but when you divide (which is the standard method), most of the health disparities appear to be increasing.

So both are true simultaneously. Which raises the question as to why dividing has become the standard? I have two explanations - one rooted in history, the other rooted in computerized estimation methods. Neither rooted in any logic the least bit related to health disparities.

The first reason has to do with the history of trying to figure out if smoking caused lung cancer. In post-war England, a couple doctors (Sir Austin Bradford Hill and Sir Richard Doll) did a series of studies to investigate whether smoking could be causally linked to lung cancer. Not surprising in retrospect, they saw that smoking had a big influence on the development of lung cancer. Whether you divide or subtract, lung cancer was clearly more common in smokers than non-smokers. But there was a pesky finding in relation to heart disease. When you subtract, it looks like smoking causes about as many heart attacks as it does lung cancer.

To their thinking, it made sense that smoking would affect the lungs, but why the heart? Fortunately, when you divide, rather than subtract, it looks like smoking has a huge influence on the risk of getting lung cancer, but is associated with only about a 20% increase in heart attacks.

From that, they concluded that dividing must be the right way to think about it.

But subtracting is just as valid mathematically. All these numbers say is that smoking causes about the same amount of heart attacks as it causes lung cancer, but because lung cancer is so rare in non-smokers, that makes a huge relative difference, while heart attacks are pretty common among non-smokers, so a small relative difference still adds up to a lot of heart attacks.

The other reason that public health types divide rather than subtract is that computers like to divide. Well, that's not really true, they don't care. But the complicated statistical methods that we ask computers to do almost all rely on dividing as the one and only way to compare two numbers. The statistical methods that rely on subtracting as much harder to implement, and are often impossible. So what I like to do is throw the complicated statistical methods out the window and calculate the differences using more labor-intensive methods.

All of which is by way of saying that next time you hear that health disparities are getting worse, take it with a grain of salt. It probably depends on how you do the numbers.

My Rip on Health Disparities Research

A few days ago, I gave my final lecture in my epi class, partly an overview of social epidemiology, and partly a rip on health disparities research.

The short version:

Identifying and describing health disparities:

- is a great way to get grant money.

- seems like a great way to raise awareness-

--- in order to mobilize greater resources to address the problem &

--- in order to mobilize members of the 'target population' to take preventive action.

- can be demoralizing to the 'target population'.

- can induce feelings of helplessness in the 'target population'.

- can make ill health seem inevitable & expected in the 'target population',

--- potentially reducing the urgency for action.

- describes the result, not the causes-

--- if you believe genetics is the cause, the existence of health disparities supports that notion

--- if you believe lifestyle is the cause, the existence of health disparities supports that notion

--- if you believe racism is the cause, the existence of health disparities supports that notion.

- don't identify potential public health actions to address health disparities

Furthermore, the almost exclusive focus on adverse health disparities:

- is demoralizing to the 'target population'.

- enhances the sense of social distance between the 'target' and 'majority' populations.

- obscures the true picture of a mixture of adverse health disparities, health similarities and advantageous health disparities.

Ignoring advantageous health disparities

- blinds us to the possibility of understanding the mechanisms for these advantages

--- which could lead to more effective public health measures built upon those mechanisms to address the adverse health disparities

--- or could lead to building on those mechanisms to improve the health of populations other than the 'target population', including the 'majority' population.