Opioid-related deaths have severely increased since 2000 in the United States. This crisis has been declared a public health emergency, and among the most affected states is Ohio. We used statewide vital statistic data from the Ohio Department of Health (ODH) and demographics data from the U.S. Census Bureau to analyze opioid-related mortality from 2010 to 2016. We focused on the characterization of the demographics from the population of opioid-related fatalities, spatiotemporal pattern analysis using Moran’s statistics at the census-tract level, and comorbidity analysis using frequent itemset mining and association rule mining. We found higher rates of opioid-related deaths in white males aged 25–54 compared to the rest of Ohioans. Deaths tended to increasingly cluster around Cleveland, Columbus and Cincinnati and away from rural regions as time progressed. We also found relatively high co-occurrence of cardiovascular disease, anxiety or drug abuse history, with opioid-related mortality. Our results demonstrate that state-wide spatiotemporal and comorbidity analysis of the opioid epidemic could provide novel insights into how the demographic characteristics, spatiotemporal factors, and/or health conditions may be associated with opioid-related deaths in the state of Ohio.

Objective: Our study focused on identifying socioeconomic factors associated with death by opioid overdose in Ohio communities at the census tract level. Materials and Methods: A large-scale vital statistic dataset from Ohio Department of Health (ODH) and U.S. Census datasets were used to obtain opioid-related death rate and socioeconomic characteristics for all census tracts in Ohio. Regression analysis was performed to identify the relationships between socioeconomic factors of census tracts and the opioid-related death rate for both urban and rural tracts. Results: In Ohio from 2010-2016, whites, males, and people aged 25-44 had the highest opioid-related death rates. At the census tract level, higher death rates were associated with certain socioeconomic characteristics (e.g. percentage of the census tract population living in urban areas, percentage divorced/separated, percentage of vacant housing units). Predominately rural areas had a different population composition than urban areas, and death rates in rural areas exhibited fewer associations with socioeconomic characteristics. Discussion: Predictive models of opioid-related death rates based on census tract-level characteristics held for urban areas more than rural ones, reflecting the recently observed rural- to- urban geographic shift in opioid-related deaths. Future research is needed to examine the geographic distribution of opioid abuse throughout Ohio and in other states. Conclusion: Regression analysis identified associations between population characteristics and opioid-related death rates of Ohio census tracts. These analyses can help government officials and law official workers prevent, predict and combat opioid abuse at the community level.

IntroductionPeripheral artery disease (PAD) disproportionately burdens Black Americans, particularly Black men. Despite the significant prevalence and high rate of associated morbidity and mortality, awareness of and treatment initiation for PAD remains low in this demographic group. To improve awareness, early detection, and treatment initiation of PAD among Black men, barbershops may be ideal settings for screening and education. MethodsA qualitative study involving 1:1 participant interviews in Cleveland, Ohio assessed perspectives of Black men about barbershop-based screening and education about PAD. Inductive thematic analysis was performed to derive themes directly from the data to reflect perceived PAD awareness and acceptability of screening in a barbershop setting. Results 28 African American/Black, non-Hispanic men completed a qualitative interview for this analysis. Mean age was 59.3±11.2 years and 93% of participants resided in socioeconomically disadvantaged zip codes. Several themes emerged indicating increased awareness of PAD and acceptability of barbershop-based screenings for PAD, advocacy for systemic changes to improve the health of the community, and a desire among participants to increase knowledge about cardiovascular disease.ConclusionsParticipants were overwhelmingly accepting of PAD screenings and reported increased awareness of PAD and propensity to seek healthcare due to engagement in the study. Participants provided insight into barriers and facilitators of health and healthcare-seeking behavior, as well as into the community and the barbershop as an institution. Additional research is needed to explore the perspectives of additional stakeholders and to translate community-based screenings into treatment initiation.

pathological analysis. By using a microarray, we found 1711 differential expression genes in the I/R injured kidneys, including 835 upregulated genes and 876 down-regulated genes. These genes were overlapped with a database from DGF vs IGF, including 1109 differential transcripts (Mueller TF, et al. Am J Transplant. 2008;8(1):78-85), and 107 overlapped differential expression genes were identified, including 79 up-regulated and 28 down-regulated genes. We found that CLCF1 was one of the most signficant upregulated genes. Results from real-time qPCR indicated that the expression of CLCF1 in the I/R injured kidneys was increased to 11.1-fold compared with the sham operated kidneys. Consistently, the protein levels of CLCF1 in both the kidney tissues and serum were increased by I/R renal injury.CONCLUSIONS: Our data indicated that CLCF1 was an I/R renal injury-induced factor, which may play an important role in the occurrence of DGF after renal transplantation. Detection of serum CLCF1 before or after renal transplantation may be helpful for the predication of DGF.

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