Elisabeth Dowling Root

Association of Neighborhood Characteristics with Bystander-Initiated CPR

BACKGROUND For persons who have an out-of-hospital cardiac arrest, the probability of receiving bystander-initiated cardiopulmonary resuscitation (CPR) may be influenced by neighborhood characteristics. METHODS We analyzed surveillance data prospectively submitted from 29 U.S. sites to the Cardiac Arrest Registry to Enhance Survival between October 1, 2005, and December 31, 2009. The neighborhood in which each cardiac arrest occurred was determined from census-tract data. We classified neighborhoods as high-income or low-income on the basis of a median household income threshold of

Increasing Cardiopulmonary Resuscitation Provision in Communities With Low Bystander Cardiopulmonary Resuscitation Rates A Science Advisory From the American Heart Association for Healthcare Providers, Policymakers, Public Health Departments, and Community Leaders

40,000 and as white or black if more than 80% of the census tract was predominantly of one race. Neighborhoods without a predominant racial composition were classified as integrated. We analyzed the relationship between the median income and racial composition of a neighborhood and the performance of bystander-initiated CPR. RESULTS Among 14,225 patients with cardiac arrest, bystander-initiated CPR was provided to 4068 (28.6%). As compared with patients who had a cardiac arrest in high-income white neighborhoods, those in low-income black neighborhoods were less likely to receive bystander-initiated CPR (odds ratio, 0.49; 95% confidence interval [CI], 0.41 to 0.58). The same was true of patients with cardiac arrest in neighborhoods characterized as low-income white (odds ratio, 0.65; 95% CI, 0.51 to 0.82), low-income integrated (odds ratio, 0.62; 95% CI, 0.56 to 0.70), and high-income black (odds ratio, 0.77; 95% CI, 0.68 to 0.86). The odds ratio for bystander-initiated CPR in high-income integrated neighborhoods (1.03; 95% CI, 0.64 to 1.65) was similar to that for high-income white neighborhoods. CONCLUSIONS In a large cohort study, we found that patients who had an out-of-hospital cardiac arrest in low-income black neighborhoods were less likely to receive bystander-initiated CPR than those in high-income white neighborhoods. (Funded by the Centers for Disease Control and Prevention and others.).

Moving Neighborhoods and Health Research Forward: Using Geographic Methods to Examine the Role of Spatial Scale in Neighborhood Effects on Health

There are approximately 360 000 out-of-hospital cardiac arrests (OHCAs) in the United States each year, accounting for 15% of all deaths.1 Striking geographic variation in OHCA outcomes has been observed, with survival rates varying from 0.2% in Detroit, MI,2 to 16% in Seattle, WA.3 Survival variation can be explained in part by differing rates of bystander cardiopulmonary resuscitation (CPR), a vital link in improving survival for victims of OHCA. For every 30 people who receive bystander CPR, 1 additional life is saved.4 Communities that have increased rates of bystander CPR have experienced improvements in OHCA survival5,6; therefore, a promising approach to increasing OHCA survival is to increase the provision of bystander CPR. Yet provision of bystander CPR varies dramatically by locale, with rates ranging from 10% to 65% in the United States.7,8 On average, however, bystander CPR is provided in only approximately one fourth of all OHCA events in the United States despite public education campaigns and promotion of CPR as a best practice by organizations such as the American Heart Association and American Red Cross.9–11 Internationally, similar variation exists, with rates of bystander CPR reported to be as low as 1%12 and as high as 44%.13 Therefore, it is important to understand why certain communities have low bystander CPR rates and to provide recommendations for how to increase bystander CPR provision in these communities. Four critical steps are involved in providing bystander CPR as part of a coordinated community emergency response (Figure 1). First, the potential rescuer must recognize that the victim needs assistance. Early recognition may include the bystander recognizing that the victim has had a cardiac arrest, or simply that the victim needs assistance from emergency medical services (EMS). Second, the …

A tale of two cities: The role of neighborhood socioeconomic status in spatial clustering of bystander CPR in Austin and Houston ☆

A rich history of research documents the effects of neighborhood-level socioeconomic status (SES) conditions on health outcomes. Recent criticism of the neighborhoods and health literature, however, has stressed several conceptual and methodological challenges not adequately addressed in previous research. Critics suggest that early work on neighborhoods and health gave little thought to the spatial scale at which SES factors influence a specific health outcome. This article discusses the concept of neighborhoods and health, reviews recent criticisms of existing work, and provides a case study that exemplifies how geographic methods can address one such criticism. Using data on birth defects in North Carolina, the case study examines the relation of SES to orofacial clefts (cleft lip and cleft palate) at different spatial scales. The Brown–Forsythe test is used to select optimal neighborhood size. Results are evaluated using logistic regression models to examine the relationship between SES measures and orofacial clefts, controlling for individual-level risk factors. Results indicate modest associations between neighborhood-level measures of poverty and cleft palate but no associations with cleft lip with or without cleft palate.

Integration of Spatial and Social Network Analysis in Disease Transmission Studies

BACKGROUND Despite evidence to suggest significant spatial variation in out-of-hospital cardiac arrest (OHCA) and bystander cardiopulmonary resuscitation (BCPR) rates, geographic information systems (GIS) and spatial analysis have not been widely used to understand the reasons behind this variation. This study employs spatial statistics to identify the location and extent of clusters of bystander CPR in Houston and Travis County, TX. METHODS Data were extracted from the Cardiac Arrest Registry to Enhance Survival for two U.S. sites - Austin-Travis County EMS and the Houston Fire Department - between October 1, 2006 and December 31, 2009. Hierarchical logistic regression models were used to assess the relationship between income and racial/ethnic composition of a neighborhood and BCPR for OHCA and to adjust expected counts of BCPR for spatial cluster analysis. The spatial scan statistic was used to find the geographic extent of clusters of high and low BCPR. RESULTS Results indicate spatial clusters of lower than expected BCPR rates in Houston. Compared to BCPR rates in the rest of the community, there was a circular area of 4.2km radius where BCPR rates were lower than expected (RR=0.62; p<0.0001 and RR=0.55; p=0.037) which persist when adjusted for individual-level patient characteristics (RR=0.34; p=0.027) and neighborhood-level race (RR=0.34; p=0.034) and household income (RR=0.34; p=0.046). We also find a spatial cluster of higher than expected BCPR in Austin. Compared to the rest of the community, there was a 23.8km radius area where BCPR rates were higher than expected (RR=1.75; p=0.07) which disappears after controlling for individual-level characteristics. CONCLUSIONS A geographically targeted CPR training strategy which is tailored to individual and neighborhood population characteristics may be effective in reducing existing disparities in the provision of bystander CPR for out-of-hospital cardiac arrest.

Socioeconomic context and gastroschisis: Exploring associations at various geographic scales

This study presents a case study of how social network and spatial analytical methods can be used simultaneously for disease transmission modeling. The article first reviews strategies employed in previous studies and then offers the example of transmission of two bacterial diarrheal diseases in rural Bangladesh. The goal is to understand how diseases vary socially above and beyond the effects of the local neighborhood context. Patterns of cholera and shigellosis incidence are analyzed in space and within kinship-based social networks in Matlab, Bangladesh. Data include a spatially referenced longitudinal demographic database that consists of approximately 200,000 people and laboratory-confirmed cholera and shigellosis cases from 1983 to 2003. Matrices are created of kinship ties among households using a complete network design and distance matrices are also created to model spatial relationships. Morans I statistics are calculated to measure clustering within both social and spatial matrices. Combined spatial effects and spatial disturbance models are built to simultaneously analyze spatial and social effects while controlling for local environmental context. Results indicate that cholera and shigellosis always cluster in space and only sometimes within social networks. This suggests that the local environment is most important for understanding transmission of both diseases, although kinship-based social networks also influence their transmission. Simultaneous spatial and social network analysis can help us better understand disease transmission and this study offers several strategies on how.

Multiple cluster analysis for the identification of high-risk census tracts for out-of-hospital cardiac arrest (OHCA) in Denver, Colorado

This study examines associations between area-level socioeconomic factors and the birth defect gastroschisis in order to further our understanding of the etiology of this condition. Specifically, this study explores how measuring socioeconomic conditions at different geographic scales affect the results of statistical models. A population-based case-control study of resident live births was conducted using data from the North Carolina Birth Defect Monitoring Program and the North Carolina composite linked birth files from 1998 through 2004. Neighborhood conditions potentially related to gastroschisis (poverty, unemployment, education, and racial composition) were measured using Census 2000 data and aggregated to several geographic scales. The Brown-Forsythe test of homogeneity of variance was used to select the neighborhood size by examining the effect of neighborhood size on variation in gastroschisis rates. To examine our assumptions about neighborhood size and neighborhood effects on gastroschisis, we estimated a series of logistic regression and multilevel logistic regression models. The Brown-Forsythe test suggested an optimal neighborhood size with a circular radius of approximately 2500 m, which was supported by the statistical analysis. Results indicate a weak association between living in a neighborhood characterized by high poverty and unemployment and an elevated risk of a gastroschisis-affected pregnancy after adjusting for individual-level risk factors. Cross-level interactions indicate that women in low poverty neighborhoods who do not rely on Medicaid have a significantly lower risk of gastroschisis. The choice of neighborhood scale influences model results suggesting that socioeconomic processes may influence health outcomes variably at different scales.

Distance to health services affects local-level vaccine efficacy for pneumococcal conjugate vaccine (PCV) among rural Filipino children

BACKGROUND Prior research has shown that high-risk census tracts for out-of-hospital cardiac arrest (OHCA) can be identified. High-risk neighborhoods are defined as having a high incidence of OHCA and a low prevalence of bystander cardiopulmonary resuscitation (CPR). However, there is no consensus regarding the process for identifying high-risk neighborhoods. OBJECTIVE We propose a novel summary approach to identify high-risk neighborhoods through three separate spatial analysis methods: Empirical Bayes (EB), Local Morans I (LISA), and Getis Ord Gi* (Gi*) in Denver, Colorado. METHODS We conducted a secondary analysis of prospectively collected Emergency Medical Services data of OHCA from January 1, 2009 to December 31, 2011 from the City and County of Denver, Colorado. OHCA incidents were restricted to those of cardiac etiology in adults ≥18 years. The OHCA incident locations were geocoded using Centrus. EB smoothed incidence rates were calculated for OHCA using Geoda and LISA and Gi* calculated using ArcGIS 10. RESULTS A total of 1102 arrests in 142 census tracts occurred during the study period, with 887 arrests included in the final sample. Maps of clusters of high OHCA incidence were overlaid with maps identifying census tracts in the below the Denver County mean for bystander CPR prevalence. Five census tracts identified were designated as Tier 1 high-risk tracts, while an additional 7 census tracts where designated as Tier 2 high-risk tracts. CONCLUSION This is the first study to use these three spatial cluster analysis methods for the detection of high-risk census tracts. These census tracts are possible sites for targeted community-based interventions to improve both cardiovascular health education and CPR training.

Protocol for a mixed-methods study of supplemental oxygen in pulmonary fibrosis

Significance Although pneumococcal conjugate vaccines (PCVs) are widely available in industrialized nations, the cost of these vaccines and the strategy of universal vaccination of infants, as endorsed by the World Health Organization, are daunting obstacles to the adoption of these vaccines in developing countries. Using spatial epidemiological methods to examine the spatial variation in vaccine efficacy (VE) in an 11-valent PCV trial in Bohol, Philippines, we suggest an alternative strategy to universal vaccination. Our main finding suggests that areas with poor access to healthcare have the highest VE. An alternative vaccination strategy could target vaccination to areas where children are most likely to benefit, rather than focus on nationwide immunization. Pneumococcal conjugate vaccines (PCVs) have demonstrated efficacy against childhood pneumococcal disease in several regions globally. We demonstrate how spatial epidemiological analysis of a PCV trial can assist in developing vaccination strategies that target specific geographic subpopulations at greater risk for pneumococcal pneumonia. We conducted a secondary analysis of a randomized, placebo-controlled, double-blind vaccine trial that examined the efficacy of an 11-valent PCV among children less than 2 y of age in Bohol, Philippines. Trial data were linked to the residential location of each participant using a geographic information system. We use spatial interpolation methods to create smoothed surface maps of vaccination rates and local-level vaccine efficacy across the study area. We then measure the relationship between distance to the main study hospital and local-level vaccine efficacy, controlling for ecological factors, using spatial autoregressive models with spatial autoregressive disturbances. We find a significant amount of spatial variation in vaccination rates across the study area. For the primary study endpoint vaccine efficacy increased with distance from the main study hospital from −14% for children living less than 1.5 km from Bohol Regional Hospital (BRH) to 55% for children living greater than 8.5 km from BRH. Spatial regression models indicated that after adjustment for ecological factors, distance to the main study hospital was positively related to vaccine efficacy, increasing at a rate of 4.5% per kilometer distance. Because areas with poor access to care have significantly higher VE, targeted vaccination of children in these areas might allow for a more effective implementation of global programs.

The Impact of Childhood Mobility on Exposure to Neighborhood Socioeconomic Context Over Time

BackgroundLittle is known about whether or how supplemental oxygen affects patients with pulmonary fibrosis.Methods/DesignA mixed-methods study is described. Patients with pulmonary fibrosis, informal caregivers of pulmonary fibrosis patients and practitioners who prescribe supplemental oxygen will be interviewed to gather data on perceptions of how supplemental oxygen impacts patients. In addition, three hundred pulmonary fibrosis patients who do not use daytime supplemental oxygen will be recruited to participate in a longitudinal, pre-/post- study in which patient-reported outcome (PRO) and activity data will be collected at baseline, immediately before daytime supplemental oxygen is initiated, and then once and again 9–12 months later. Activity data will be collected using accelerometers and portable GPS data recorders. The primary outcome is change in dyspnea from before to one month after supplemental oxygen is initiated. Secondary outcomes include scores from PROs to assess cough, fatigue and quality of life as well as the activity data. In exploratory analyses, we will use longitudinal data analytic techniques to assess the trajectories of outcomes over time while controlling for potentially influential variables.DiscussionThroughout the study and at its completion, results will be posted on the website for our research program (the Participation Program for Pulmonary Fibrosis or P3F) at http://www.pulmonaryfibrosisresearch.org.