I’ve spent a good part of the summer taking a deep dive into several pots of economic and education data with an eye toward fleshing out a couple of chapters in the book version of TIGC. As a result, I’ve been neglecting the blog.
Then, in mid-August, I got a call asking me to make a presentation to this year’s opening session of the Georgia House Rural Development Council (HRDC) on September 1st. Over the years, I’ve given more than 50 presentations on my TIGC work, and generally I’ll update or amend my PowerPoint with whatever new data I’ve been working on. The result has been that the presentation has devolved, in my view, into a bit of mishmash.
Now I’ve been asked to speak in mid-November to a symposium on the state’s urban-rural divide and, with about six weeks to work, I’ve decided to do a major overhaul on my presentation — and to write an occasional post as I do so.
This is the first of those posts. My plan right now is to create a series of slides built around the theme of “gauging the gap” between Metro Atlanta and the rest of the state.
I started this process yesterday by updating my research and analysis of the state’s county-level premature death rates. I use premature death rates — formally known as “Years of Potential Life Lost before Age 75,” or YPLL 75 — as a proxy for community health status.
I’m sure I can get a fair argument that this approach is insufficient or an oversimplification, but, as an old public health friend once explained to me, “Premature death is the Dow Jones Industrial Average of population health.
“If you want to look at one number and get a feel for a community’s health status, look at premature death,” he said. Backing up that assessment is the fact that County Health Rankings & Roadmaps uses premature death rates as a key component in evaluating health outcomes for more than 3,000 U.S. counties.
Another reason I like using YPLL 75 rates is that they’re simple to calculate. Working with age data mined from death certificates submitted to the state, the Georgia Department of Public Health (DPH) keeps track of all the years of potential life lost before age 75 for all the counties in the state on an annual basis and posts this data to its excellent public health database.
If a 50-year-old Macon man dies, he contributes 25 years to Bibb County’s bucket of years of potential life lost before age 75. A 74-year-old woman up in Clayton, Ga.? That’s a year on Rabun County’s tally. A six-month-old infant in Decatur? That goes down as 74-and-a-half years for DeKalb County. And so on.
The DPH database also includes annual population estimates generated by the U.S. Census Bureau, and that’s really all you need to calculate YPLL 75 (or Premature Death) Rates. The formula is:
(YPLL 75/YPLL 75 Population) X 100,000 = YPLL 75 Rate
As a couple of examples, Forsyth County had Georgia’s best YPLL 75 rate in 2020 and Clay County had the worst. In fast-growing Forsyth County, the total number of years of potential life lost before age 75 was 9,970. Divide that by the county’s YPLL 75 population (the number of people 75 or younger) of 238,043 and multiply the result by 100,000 and you get a YPLL 75 rate of 4,188.3. I haven’t double-checked this, but I’ll guarantee you that premature death rate is among the best in the country.
Tiny, poverty-stricken Clay County, located hard on the Alabama line in southwest Georgia, turned in true third-world numbers for 2020 — a YPLL 75 Rate of 22,180.6 (basically five times worse than Forsyth County).
(Its data also generated something of a riddle. With a YPLL 75 population of just over 2,500 people, its YPLL 75 total more than doubled from 2019 to 2020 — jumping from 253 to 562.5.
(When I saw that big increase in years of potential life lost, my first reaction was that Clay County had gotten clobbered by Covid-19. Adding to that line of speculation was the fact that the total number of deaths in the county actually dropped to 45 in 2020 from 57 in 2019, and I immediately figured the virus had claimed a number of relatively young people in the county. That wasn’t a crazy notion. Clay County has little if any healthcare infrastructure and isn’t that far from Albany, which at one point last year was the global ground zero for the virus.
(But no. A quick check of DPH’s Covid-19 data reveals that Clay County suffered only four Covid-19 deaths in 2020 (and none so far this year) — and only two of those victims were under the age of 75. Together they contributed only 28 years to the county’s total YPLL 75 pot of 562.5 years.
(So what was killing younger people in Clay County? A review of the cause-of-death data in DPH’s OASIS database didn’t turn up many significant differences over 2019 — until I got down to the External Causes category. In 2019, the county reported no suicides or poisoning deaths. In 2020, there were three poisoning deaths and four suicides, all under the age of 75. Indeed, four were under 50; that’s at least 100 years of potential life lost before the age of 75 right there.
(Were the suicides or poisoning deaths some sort of collateral damage from Covid-19? I don’t know, but I’m curious enough to check and see if similar patterns turn up other counties.)
I have, however, meandered. To tie off this incredibly laborious math explanation I started about a half-dozen paragraphs up, here are the numbers for Georgia’s best and worst YPLL 75 counties.
Now back to my original objective — a comparison of premature death rates between my TIGC 12-county Metro Atlanta region and the state’s other 147 counties. (I should probably acknowledge that I’ve waffled on the question of how best to analyze the data I’ve collected. I’ve looked at using a basic North Georgia/South Georgia split as well the five regions I created early on in this process. At times I’ve analyzed county data based on their political leanings. For the purposes of this upcoming presentation (and these blog posts) I’ve decided to try to keep it simple and just compare Metro Atlanta to the rest of the state.)
This chart shows the YPLL 75 performance for TIGC’s 12-county Metro Atlanta region versus the state’s Other 147 Counties from 1994 (the earliest year for which DPH has data) through 2020. With YPLL 75 Rates, the lower the number, the better, so Metro Atlanta’s blue line at the bottom of this chart signifies the better peformance.
There are several important takeaways from this chart. The first is that the gap between Metro Atlanta the rest of Georgia has been widening throughout the 26-year period. In 1994, Metro Atlanta had what might be described as a 15.8 percent premature death “advantage” over the rest of the state; by 2020, that “advantage” was up to 41 percent. As I’ll get into in future posts, these differences have implications both for healthcare costs and for economic productivity.
A second takeaway has to do with what began happening in about 2011. Up until then, both Metro Atlanta and the rest of the state had generally been gaining ground, if somewhat unevenly. But that pretty much came to a halt in 2010, and in 2011 the entire state’s YPLL 75 Rate ticked up (that is, got worse). Metro Atlanta regained some ground in 2012, but then saw its YPLL 75 Rate deteriorate a little or flatline every year for the next five years before finally posting some improvement in 2018 and 2019.
The Other 147 Counties fared worse over that same period. If Metro Atlanta’s YPLL 75 Rate performance produced a five-year plateau from 2013 through 2017, the rest of the state generated a couple of uphill climbs before finally finding a downhill slope and producing three straight years of (slightly) improving numbers. But then came 2020 and Covid-19 — and the YPLL 75 Rates took off like moonshots.
Back to the takeaways. Back in 2011 and ’12, as I was starting work on Trouble in God’s Country and just beginning to dig into the premature death data, I remember noticing the sudden uptick in YPLL 75 Rates but didn’t know what to make of them. Over time — and in combination with similar adverse trends in other data — I’ve come to believe that what I was seeing amounted to aftershocks from the Great Recession. It showed up in economic, education and even birth and death data, and in every case, the Other 147 Counties suffered a harder blow than Metro Atlanta.
What to make, then, of the modest gains that began showing up in 2017 and ’18? As it happens, I’m seeing similar patterns in other datasets. I discussed those in my HRDC presentation a few weeks ago, but hadn’t yet started this review of YPLL 75 Rates. In isolation, I wouldn’t attach much significance to any one instance of improvement, but in combination I think they signal that my Great Recession aftershocks may finally be playing themselves out.
Now, though, we have Covid-19, and its impact across a range of societal sectors — health, economics, education — is already profound. The question is whether it will generate its own wave of aftershocks that will be with us for years to come.