Suicide rates have increased in the U.S. over the past 15 years with substantial geographic variation in these increases; yet there have been few attempts to cluster counties by the magnitude of suicide rate changes by intercept and slope or to identify the economic precursors of increases. We used Vital Statistics data and growth mixture models to identify clusters of counties by their magnitude of suicide growth from 2008 to 2020 and examined associations with county economic and labor indices. Our models identified five clusters, each differentiated by intercept and slope magnitude, with the highest rate cluster (4% of counties) mainly in sparsely populated areas in the West and Alaska, starting the time series at 25.4 suicides/100,000, and exhibiting the steepest increase in slope (0.69/100,000 per year). There was no cluster for which the suicide rate was stable or declining. Counties in the highest rate cluster were more likely to have agriculture and service economies, and less likely to have urban professional economies. Given the increased burden of suicide, with no clusters of counties improving over time, additional policy and prevention efforts are needed, particularly targeted at rural areas in the West.