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Racial Disparities in Spatial and Temporal Youth Suicide Clusters
Jonathan M Platt1, John R Pamplin2, Catherine Gimbrone3
1University of Iowa College of Public Health, Iowa City.
Objective:
Deaths by suicide correlate both spatially and temporally, leading to suicide clusters. This study aimed to estimate racial patterns in suicide clusters since 2000.
Method:
Data from the US National Vital Statistics System included all International Classification of Diseases, Tenth Revision (ICD-10)-coded suicide cases from 2000-2019 among American Indian/Alaska Native (AI/AN), Asian/Pacific Islander (A/PI), Black, or White youth and young adults, aged 5-34 years. We estimated age, period, and cohort (APC) trends and identified spatiotemporal clusters using the SaTScan space-time statistic, which identified lower- and higher-than-expected suicide rates (cold and hot clusters) in a prespecified area (150 km) and time interval (15 months). We also calculated the average proportion of deaths by suicide contained in clusters, to quantify the relative importance of spatiotemporal patterning as a driver of overall suicide rates.
Results:
From 2010-2019, suicide rates increased from between 37% among AI/AN (95% CI = 1.22, 1.55) to 81% among A/PI (95% CI = 1.65, 2.01) groups. Suicide clusters accounted for 0.8%-10.3% of all suicide deaths, across racial groups. Since 2000, the likelihood of detecting cluster increased over time, with considerable differences in the number of clusters in each racial group (4 among AI/AN to 72 among White youth). Among Black youth and young adults, 27 total clusters were identified. Hot clusters were concentrated in southeastern and mid-Atlantic counties.
Conclusion:
Suicide rates and clusters in youth and young adults have increased in the past 2 decades, requiring attention from policy makers, clinicians, and caretakers. Racially distinct patterns highlight opportunities to tailor individual- and population-level prevention efforts to prevent suicide deaths in emerging high-risk groups.
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Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...

