{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T11:48:00Z","timestamp":1782215280232,"version":"3.54.5"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2015,3,3]],"date-time":"2015-03-03T00:00:00Z","timestamp":1425340800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CJEM"],"published-print":{"date-parts":[[2015,5]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec id=\"S1481803514000402_abs1\" sec-type=\"general\"><jats:title>Background<\/jats:title><jats:p>Traditional variables used to explain survival following out-of-hospital cardiac arrest (OHCA) account for only 72% of survival, suggesting that other unknown factors may influence outcomes. Research on other diseases suggests that neighbourhood factors may partly determine health outcomes. Yet, this approach has rarely been used for OHCA. This work outlines a methodology to investigate multiple neighbourhood factors as determinants of OHCA outcomes.<\/jats:p><\/jats:sec><jats:sec id=\"S1481803514000402_abs2\" sec-type=\"methods\"><jats:title>Methods<\/jats:title><jats:p>A retrospective, observational cohort study design will be used. All adult non-emergency medical service witnessed OHCAs of cardiac etiology within the city of Toronto between 2006 and 2010 will be included. Event details will be extracted from the Toronto site of the Resuscitation Outcomes Consortium Epistry\u2014Cardiac Arrest, an existing population-based dataset of consecutive OHCA patients. Geographic information systems technology will be used to assign patients to census tracts. Neighbourhood variables to be explored include the Ontario Marginalization Index (deprivation, dependency, ethnicity, and instability), crime rate, and density of family physicians. Hierarchical logistic regression analysis will be used to explore the association between neighbourhood characteristics and 1) survival-to-hospital discharge, 2) return-of-spontaneous circulation at hospital arrival, and 3) provision of bystander cardiopulmonary resuscitation (CPR). Receiver operating characteristics curves will evaluate each model\u2019s ability to discriminate between those with and without each outcome.<\/jats:p><\/jats:sec><jats:sec id=\"S1481803514000402_abs3\" sec-type=\"discussion\"><jats:title>Discussion<\/jats:title><jats:p>This study will determine the role of neighbourhood characteristics in OHCA and their association with clinical outcomes. The results can be used as the basis to focus on specific neighbourhoods for facilitating educational interventions, CPR awareness programs, and higher utilization of automatic defibrillation devices.<\/jats:p><\/jats:sec>","DOI":"10.1017\/cem.2014.40","type":"journal-article","created":{"date-parts":[[2015,3,3]],"date-time":"2015-03-03T15:01:29Z","timestamp":1425394889000},"page":"286-294","source":"Crossref","is-referenced-by-count":4,"title":["Does location matter? 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