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Objective: This study sought to investigate the correlation between community methamphetamine use, gauged by overdose mortality rates, and incidence of violent crime. Method: We carried out a descriptive, cross-sectional analysis of county-level data from multiple public sources, involving all 3147 US counties. Methamphetamine overdose rates for the year 2019 were derived from CDC WONDER, while violent crime rates were collected from NIBRS. Results: Our data set contained 522 counties with complete information, largely metro (92.72%). Overdose data was suppressed for 2625 counties—697 (26.55%) metro, and 1928 (73.45%) non-metro, hence multiple imputation was utilized for comprehensive results. The analysis showed significant correlations between methamphetamine overdose and all violent crime, and specifically robbery (F = 5.55, P =.005 and F = 47.60, P <.001, respectively). Conclusion: Our study suggests that communities with higher methamphetamine overdoses likely face increased rates of crime, specifically robbery, which could impact costs associated with law enforcement, prosecution, and healthcare. The study offers valuable insights for law enforcement and policymakers, and underlines the need for further research to fully understand the dynamics of methamphetamine use and violence at the community level. [ABSTRACT FROM AUTHOR]

Background: Developmental trauma depending on several factors may lead to later adult health risks and is an increasing public health concern, especially in states with predominantly rural populations. Oklahoma remains one of the states in America with the highest count of adverse childhood experiences (ACEs); therefore, more refined research methods for quantifying ACEs are vital for ensuring proper statewide interventions., Objective: While data sets already exist at the state level measuring specific ACEs like divorce or child abuse, the state currently lacks a single source for specific ACEs that can incorporate regions to allow for the identification of counties where ACEs are especially high. This county identification will allow for assessing trends in adversity prevalence over time to indicate where targeted interventions should be done and which counties experience amplified long-term consequences of high ACE rates. Thus, the model for the Oklahoma Adversity Surveillance Index System (OASIS) was born-a public health tool to map ACEs at the county level and grade them by severity over time., Methods: County-level data for 6 ACEs (mental illness, divorce, neglect, child abuse, domestic violence, and substance use) were collected from the Oklahoma Department of Human Services, Oklahoma State Department of Health, and Oklahoma Community Mental Health Centers for the years 2010 to 2018. First, a potential ACEs score (PAS) was created by standardizing and summing county rates for each ACE. To examine the temporal change in the PAS, a bivariate regression analysis was conducted. Additionally, an ACEs severity index (ASI) was created as a standardized measure of ACE severity across time. This included scoring counties based on severity for each ACE individually and summing the scores to generate an overall ASI for each county, capturing the severity of all ACEs included in the analysis., Results: Mental illness and substance use showed the highest rates at the state level. Results from the regression were significant (F 1,7 6 =5.269; P=.02), showing that county PAS showed an increase over years. The ASI scores ranged from 0 to 6, and 4 Oklahoma counties (Adair, McCurtain, Muskogee, and Pittsburg) received a score of 6., Conclusions: OASIS involves the identification of counties where ACEs are most prevalent, allowing for the prioritization of interventions in these "hot spot" counties. In addition, regression analysis showed that ACEs increased in Oklahoma from 2010 to 2018. Future efforts should center on adding additional ACEs to the ASI and correlating adverse outcome rates (such as violence and medical disorder prevalence) at the county level with high ASI scores., (©Jason Walter Beaman, Cherie Josephine Miner, Cadence Bolinger. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 22.08.2023.)