Chicken and the Egg
In the four years we’ve been talking about the relationship between health and economic vitality at a community level, the one question we’ve gotten more than any other is the chicken-and-egg question. Which comes first? Which is the driver? Does health make wealth? Or vice versa?
My answer is that the relationship between health and economic productivity is pretty clear first and foremost at a personal level. We all know we’re more productive when we’re in good health than when we’re down with a cold or the flu, let alone something more serious. We also know that when we’re sick, we inevitably have to divert some of our income to medical care.
The same thing plays out at a community level. Recently we updated an analysis of the Georgia counties that came in at the top and bottom of our 2013 Partner Up! for Public Health Power Rankings – Oconee County at the top and side-by-side South Georgia neighbors Crisp and Wilcox counties tied for last.
Oconee County, a fast-growing suburban county outside Athens, has some of the best health outcome numbers – for things like premature death, percent of the population reporting being in fair or poor health, percent of babies born at a low birth weight, etc. – that you’ll find anywhere in the country. Crisp and Wilcox, adjoining neighbors in the south central part of the state, have some of the worst; among other things, both counties’ premature death rates are more than double Oconee’s.
To see whether those results rippled into available data on economic productivity and the consumption of healthcare resources, we went to the Georgia Department of Revenue for its most recent county-level data for adjusted gross income (2009) and to the Georgia Department of Community Health for its most recent county-level data on Medicaid spending (2012). The results could not have been more telling.
As it happens, Oconee County and Crisp and Wilcox combined had almost identical populations in the 2010 U.S. Census – 32,808 for Oconee and 32,694 for Crisp-Wilcox. But that’s where the similarity ends. Healthy and economically vibrant Oconee County produced $40.2 million in 2009 income tax revenue for the state government while consuming only $11.2 million in 2012 Medicaid dollars. Poor and unhealthy Crisp-Wilcox produced only $11.9 million in 2009 income taxes but consumed a whopping $44.2 million in Medicaid resources.
As stunning as those numbers are, they still don’t answer the chicken-and-egg question. If we could wave a magic wand and make everybody in Crisp-Wilcox as healthy as their counterparts in Oconee, would the Crisp-Wilcox economy automatically improve? Well, probably, at least to some degree – if only because you’d have lower healthcare costs and therefore more money available for more productive uses. But you’ve got to have something to organize a more vibrant economy around, and that’s still a problem.
Conversely, if Oconee County were to be crippled economically – if, for instance, the University of Georgia weren’t located next door in Clarke County – would health status in Oconee automatically decline? Again, probably. Without a critical mass of strong economic drivers (including a well-educated and most likely health conscious population), Oconee would not have been able to build and support the healthcare infrastructure that helps keep its population so healthy.
So the chicken-and-egg question is complicated and the answer depends on a lot of variables.
All that said, one part of our effort to answer that question has been to study all the health and economic data we’ve compiled to see what kind of patterns and synergies emerge up and down the list.
We first touched on this in an earlier blog in April. Then, we noted that the top ranks of our Power Ratings were very stable while the bottom was more volatile. That was and is true, but at that point we hadn’t had much time to study the middle ranks. Now that we have, we need to amend our observation slightly.
A couple of important notes on methodology. In this analysis, we’re only working with 156 of Georgia’s 159 counties; three – Echols, Taliaferro and Webster – were too small to generate usable health data in some of the study years, so we excluded them. For each of the four study years, we divided the remaining 156 counties into quintiles, putting 31 counties in each of the top two and bottom two quintiles, and 32 in the middle quintile.
Next came the question of how to measure stability within these quintiles. Three readily observable gauges bubbled up from the Power Ratings data:
Stability: We defined this as the number of counties that held their positions in a given quintile for all four years of the study period.
Churn: Basically, this is the number of counties that moved in and out of a quintile from year to year. In this measure, we counted counties that were in a quintile for at least one year.
Volatility: This is the difference between the highest and lowest ranks held by any county in any year for each quintile.
There are no doubt more sophisticated and statistically reliable means of analyzing this data, but this seemed like a reasonable approach to taking a first snapshot of the data.
As it works out, the bottom group of counties – while more volatile than the top rank – is actually, narrowly, the second most stable grouping of counties. Most of the instability and volatility is in the middle ranks. The trend we found is that the rankings are stable at the top, but become less stable and more volatile as we move through successively lower tiers – until we get to the bottom, where the rankings re-stabilize to some degree. The data is summarized in the table below.
The most obvious takeaways from this exercise are that if a county can get its health and economic engines to a point that they’re hitting on all cylinders and climb into the top quintile, it’s got a good chance of staying there; it’s going to be hard to dislodge. Similarly, if its economy is in the tank and its health status is poor, it’s going to have a tough time getting off the bottom of the barrel; in fact, it’s unlikely it can expect to make much progress absent significant state or even federal intervention.
Here’s the data:
Stability:Number of counties in this quintile for all four years
|Churn:Number of additional counties in this quintile for between one and three years||Volatility:|
|Highest Power Ranking by any county in this quintile in any year||Lowest Power Ranking by any county in this quintile in any year||Difference (Volatility)|
|First Quintile (Top)||27||9||1st||39th||38|
|Fifth Quintile (Bottom)||16||30||94th||156th||62|