Bystander Cardiopulmonary Resuscitation Is Clustered and Associated With Neighborhood Socioeconomic Characteristics: A Geospatial Analysis of Kent County, Michigan

• Published in: Academic emergency medicine Vol. 24; no. 8; pp. 930 - 939
• Main Authors: Uber, Amy, Sadler, Richard C., Chassee, Todd, Reynolds, Joshua C., Smith, Stephen W.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.08.2017
• Subjects: Adolescent; Adult; Aged; Cardiopulmonary resuscitation; Cardiopulmonary Resuscitation - statistics & numerical data; Case-Control Studies; Child; Child, Preschool; Cluster Analysis; CPR; Datasets; Defibrillators; Emergency medical care; Female; Geography; Humans; Infant; Infant, Newborn; Logistic Models; Male; Michigan; Middle Aged; Odds Ratio; Out-of-Hospital Cardiac Arrest - therapy; Prevalence; Residence Characteristics - statistics & numerical data; Rural areas; Socioeconomic Factors; Spatial Analysis; Young Adult; United States > US; Michigan
• ISSN: 1069-6563; 1553-2712; 1553-2712
• DOI: 10.1111/acem.13222

Objectives Geographic clustering of bystander cardiopulmonary resuscitation (CPR) is associated with demographic and socioeconomic features of the community where out‐of‐hospital cardiac arrest (OHCA) occurred, although this association remains largely untested in rural areas. With a significant rural component and relative racial homogeneity, Kent County, Michigan, provides a unique setting to externally validate or identify new community features associated with bystander CPR. Using a large, countywide data set, we tested for geographic clustering of bystander CPR and its associations with community socioeconomic features. Methods Secondary analysis of adult OHCA subjects (2010–2015) in the Cardiac Arrest Registry to Enhance Survival (CARES) data set for Kent County, Michigan. After linking geocoded OHCA cases to U.S. census data, we used Moran's I‐test to assess for spatial autocorrelation of population‐weighted cardiac arrest rate by census block group. Getis‐Ord Gi statistic assessed for spatial clustering of bystander CPR and mixed‐effects hierarchical logistic regression estimated adjusted associations between community features and bystander CPR. Results Of 1,592 subjects, 1,465 met inclusion criteria. Geospatial analysis revealed significant clustering of OHCA in more populated/urban areas. Conversely, bystander CPR was less likely in these areas (99% confidence) and more likely in suburban and rural areas (99% confidence). Adjusting for clinical, demographic, and socioeconomic covariates, bystander CPR was associated with public location (odds ratio [OR] = 1.19; 95% confidence interval [CI] = 1.03–1.39), initially shockable rhythms (OR = 1.48; 95% CI = 1.12–1.96), and those in urban neighborhoods (OR = 0.54; 95% CI = 0.38–0.77). Conclusions Out‐of‐hospital cardiac arrest and bystander CPR are geographically clustered in Kent County, Michigan, but bystander CPR is inversely associated with urban designation. These results offer new insight into bystander CPR patterns in mixed urban and rural regions and afford the opportunity for targeted community CPR education in areas of low bystander CPR prevalence.