TY - JOUR
T1 - Geographic Variation, Economic Activity, and Labor Market Characteristics in Trajectories of Suicide in the United States, 2008–2020
AU - Keyes, Katherine M.
AU - Kandula, Sasikiran
AU - Martinez-Ales, Gonzalo
AU - Gimbrone, Catherine
AU - Joseph, Victoria
AU - Monnat, Shannon
AU - Rutherford, Caroline
AU - Olfson, Mark
AU - Gould, Madelyn
AU - Shaman, Jeffrey
N1 - Publisher Copyright:
© The Author(s) 2023.
PY - 2024/2/1
Y1 - 2024/2/1
N2 - Suicide rates in the United States have increased 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 according to 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 5 clusters, each differentiated by intercept and slope magnitude, with the highest-rate cluster (4% of counties) being observed mainly in sparsely populated areas in the West and Alaska, starting the time series at 25.4 suicides per 100,000 population, and exhibiting the steepest increase in slope (0.69/100,000/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 agricultural 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.
AB - Suicide rates in the United States have increased 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 according to 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 5 clusters, each differentiated by intercept and slope magnitude, with the highest-rate cluster (4% of counties) being observed mainly in sparsely populated areas in the West and Alaska, starting the time series at 25.4 suicides per 100,000 population, and exhibiting the steepest increase in slope (0.69/100,000/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 agricultural 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.
KW - economic factors
KW - epidemiologic methods
KW - growth mixture modeling
KW - suicide
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U2 - 10.1093/aje/kwad205
DO - 10.1093/aje/kwad205
M3 - Article
C2 - 37846128
AN - SCOPUS:85183945957
SN - 0002-9262
VL - 193
SP - 256
EP - 266
JO - American Journal of Epidemiology
JF - American Journal of Epidemiology
IS - 2
ER -