My 15-year trip down this Trouble in God’s Country rabbit hole started as the result of the almost accidental discovery of a massive gap in population health between Georgia’s most and least healthy counties. I was conducting some research for a public health-related campaign my public relations firm was managing, and I was looking specifically at county-level premature death rates. Known formally as Years of Potential Life Lost Before Age 75 (or YPLL 75), the measure is generally regarded as the bestg single measure of a community’s health status. As a Georgia public heatlh official put it to me years ago, “it’s the Dow Jones Industrial Average of population health.”

It’s also a measure that’s easy enough to track and calculate, thanks to the Georgia Department of Public Health (DPH). DPH maintains an excellent, publicly accessible database known as OASIS — for Online Analytical Statistical Information System — that serves as a repository for all manner of health-related data going back to 1994. Without OASIS and that data, TIGC probably never would have gotten off the ground.

Since beginning this work in about 2010, I have obviously branched out and analyzed a wide range of other socioeconomic measures. I’ve continued to track YPLL 75 rates, but it’s been a while since I’ve written much about it. The main reason for that is I try, whenever possible, to put the socioeconomic behavior of Georgia’s 159 counties into a national context. With per capita income and educational attainment data, for instance, I’ve been able to rank all 3,000-plus counties in the United States and show how Georgia counties fare in those national data pools.

With premature death rates, that’s always been a little tougher. Part of this is my fault; I’ve never gotten to be quite as adept at mucking around in CDC and other federal health databases as I have, say, Census Bureau, U.S. Bureau of Economic Analysis, or USDA resources. Fortunately, a terrific non-profit organization known as County Health Rankings & Roadmaps came along about 15 years ago and began doing a lot of that work for me. So, I’ve relied on them and their YPLL 75 calculations to build the national premature death datasets that I use to determine how Georgia stacks up against the rest of the country.

CHRR’s 2025 report came out a couple of months ago and I finally got around to going through it recently. I downloaded CHRR’s national dataset, went immediately to their premature death data, and discovered, to my horror, that they had modified the way they calculated premature death rates. One result of this change was that it enabled CHRR’s data geeks to calculate an arguably more precise and richer picture of premature death for the 3,088 counties in their dataset. Another result was that it caused my head to explode.

Anytime you try to match or combine comparable data from different sources, there’s always a certain amount of data wrangling to be done. In the past, I’ve been able to reconcile the state’s OASIS data with CHRR’s data, or at least come close. Not this time. This year, after spending an embarassing amount of time trying and failing to fit their calculations to the state’s, I emailed CHRR and received a detailed explanation from one of their data gurus. It made sense, but I probably couldn’t do it justice with any explanation I might attempt, and I can promise you that even a brief explanation would cause most readers’ eyes to glaze over. For now, suffice it to say I’ve decided to show key pieces from both sets of data in the sortable table below.

With that, some prefacing notes and takeaways:

1. CHRR averaged YPLL 75 and YPLL 75 Population data for the years 2020 through 2022 in doing their calculations. I’ve done the same thing using OASIS data.
2. The five columns below should be fairly self-explanatory, but at least one note may be in order. The third, fourth, and fifth columns show, respectively, each county’s national rank based on the CHRR data; the in-state rank based on those national rankings, and the in-state rank based on Georgia DPH’s OASIS data. I’m using both sets of state rankings so readers can see the similarities and differences between the two. For example, Forsyth, Oconee and Cherokee counties came in 1st, 2nd and 3rd based on both the CHRR and OASIS data; the 4th, 5th and 6th places were occupied by Cobb, Fayette and Gwinnett counties, although not in the same order. The picture at the bottom of the list was comparable. Of the six counties at the bottom of CHRR’s rankings, all but one also at the bottom of the OASIS-based rankings, although the order was a little scrambled.
3. As mentioned above, I try wherever possible to put the socioeconomic performance of Georgia’s counties into a national context. With various economic and education-related datasets, I’ve found that a disproportionate share of Georgia’s counties — and population — live in counties that rank in the bottom national quartile. That’s true in this analysis as well. Based on the CHRR data, 76 of Georgia’s 159 counties are in the bottom national quartile for premature death and another 46 are in the 3rd quartile; only nine made the top quartile. As was the case with per capita income and educational attainment, Georgia has more counties in the bottom quartile for premature death than any other state in the nation, including Texas. The map above shows the distribution, with my usual color-coding.
4. This analysis gives us another basis for demonstrating the extent of the chasm between Georgia’s best-off and worst-off counties. Based on the CHRR data, Forsyth County, in the north Atlanta ‘burbs, ranked 38th nationally with a “Premature Death raw value” of 4,415.9; at the bottom of the Georgia list, Miller County ranked 3,062nd out of 3,088 counties and had a “Premature Death raw value” of 22,798.7. With any premature death measure, lower is better. The Forsyth County rating is pretty close to optimal, while Miller County’s puts it deep into Third World territory.
5. It’s worth noting that this poor premature death performance is not solely the province of Georgia’s rural counties. Among Georgia’s bottom national quartile counties in this latest premature death analysis were Macon-Bibb (2,785th nationally); Columbus-Muscogee (2,505th); Dougherty (2,853rd); Tift (2,496th); Laurens (2,794th), and, last but hardly least, Augusta-Richmond (2,674th), the site of the state’s largest public medical school. In other words, with few exceptions, the major population centers south of the gnat line aren’t performing that much better than their rural neighbors.

I’ll have more on this later. I’m working with DPH’s OASIS data to determine how different counties and areas of the state have evolved over time, and I’m using the CHRR data for another comparison between Georgia and North Carolina. For now, here’s a sortable table with key data points for each county.

Stay tuned.