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Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims
Resuscitation (2008) 79, 417—423
available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/resuscitation
Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims夽 C. Vaillancourt a,b,∗, A. Lui a, V.J. De Maio d, G.A. Wells a,c, I.G. Stiell a,b a
Ottawa Health Research Institute, University of Ottawa, Ottawa, Ontario, Canada Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada c Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada d Emergency Services Institute, WakeMed Health and Hospitals, Raleigh, NC, USA b
Received 1 March 2008; received in revised form 1 July 2008; accepted 17 July 2008
KEYWORDS Heart arrest; Asystole; Sudden cardiac death; Resuscitation; Socioeconomic factors; Social class
Summary Objectives: While lower socioeconomic status is associated with lower level of education and increased incidence of cardiovascular diseases, the impact of socioeconomic status on out-ofhospital cardiac arrest outcomes is unclear. We used residential property values as a proxy for socioeconomic status to determine if there was an association with: (1) bystander CPR rates and (2) survival to hospital discharge for out-of-hospital cardiac arrest. Methods: We performed a secondary data analysis of cardiac arrest cases prospectively collected as part of the Ontario Prehospital Advanced Life Support study, conducted in 20 cities with ALS and BLS-D paramedics. We measured patient and system characteristics for cardiac arrests of cardiac origin, not witnessed by EMS, occurring in a single residential dwelling. We obtained property values from the Municipal Property Assessment Corporation. Analyses included descriptive statistics with 95% CIs and stepwise logistic regression. Results: Three thousand six hundred cardiac arrest cases met our inclusion criteria between 1 January 1995 and 31 December 1999. Patient characteristics were: mean age 69.2, male 67.8%, witnessed 44.7%, bystander CPR 13.2%, VF/VT 33.8%, time to vehicle stop 5:36 min:s, return of spontaneous circulation 12.7%, and survival 2.7%. Median property value was $184,000 (range $25,500—2,494,000). For each $100,000 increment in property value, the likelihood of receiving bystander CPR increased (OR = 1.07; 95% CI 1.01—1.14; p = 0.03) and survival decreased (OR = 0.77; 95% CI 0.61—0.97; p = 0.03). Conclusions: This is the largest study showing an association between socioeconomic status and survival, and the first study showing an association with bystander CPR. Our findings suggest targeting CPR training among lower socioeconomic groups. © 2008 Elsevier Ireland Ltd. All rights reserved.
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at doi:10.1016/j.resuscitation.2008.07.012. ∗ Corresponding author. Tel.: +1 613 798 5555x17012; fax: +1 613 761 5351. E-mail address: [email protected] (C. Vaillancourt).
0300-9572/$ — see front matter © 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.resuscitation.2008.07.012
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C. Vaillancourt et al.
Introduction
Setting
Cardiovascular disease is the leading cause of mortality in North America, and results in almost 700,000 deaths annually in the United States.1 More than 50% of all cardiovascular disease deaths are caused by sudden cardiac arrest,2 defined as the cessation of cardiac mechanical activity resulting in the absence of vital signs.3 Cardiac arrest is the first manifestation of cardiovascular disease in over 40% of victims.4 A typical victim is a male in his sixties, and 85% of outof-hospital cardiac arrests occur in private residences.5,6 The survival rate from out-of-hospital cardiac arrest rarely exceeds 5%.7 Those who survive maintain a level of functioning similar to that of a similar age group in the general population.8 Patient age, gender, initial cardiac rhythm, bystander CPR and early defibrillation are all factors known to influence outcomes for cardiac arrest patients.9 In addition to those factors, a victim’s socioeconomic status may also influence outcomes for out-of-hospital cardiac arrest.10 Socioeconomic status is a measure of an individual’s place within a social group based on various factors, including income and education. We know that risk factors for cardiovascular disease are more prevalent among individuals with lower socioeconomic status.11 Consequently, the incidence of coronary artery disease,12 death due to myocardial infarction,13 and sudden cardiac arrest14 is also higher among these individuals. In addition, longer delays in accessing emergency medical services (EMSs) care for chest pain have been observed in lower socioeconomic status neighborhoods,15 and lower bystander CPR rates have been observed in neighborhoods of different ethnic background.16 That being said, recent studies failed to show an association between an aggregate measure of socioeconomic status (median neighborhood income), and survival to hospital discharge for out-of-hospital cardiac arrest.17—19 Because socioeconomic status can vary greatly among individuals living within a given neighborhood, we believe an individual measure of socioeconomic status (residential property value) may better reflect the influence of socioeconomic status on out-of-hospital cardiac arrest outcomes. While lower socioeconomic status is associated with lower level of education and increased incidence of cardiovascular diseases, the impact of socioeconomic status on out-of-hospital cardiac arrest outcomes is unclear. The overall purpose of this study is to better understand the influence of socioeconomic status on out-of-hospital cardiac arrest outcomes. More specifically, we will use the patient’s residential property value as a proxy for their socioeconomic status to determine: (1) the association between socioeconomic status and bystander CPR rates and (2) The association between socioeconomic status and survival for out-of-hospital cardiac arrest.
The OPALS study was designed to evaluate the sequential survival benefit of implementing an early defibrillation program followed by advanced life support for out-of-hospital cardiac arrest patients. The OPALS study took place in 20 cities equipped with basic life support-defibrillation (BLS-D) and advanced care paramedics. 9-1-1 dispatch-assisted CPR instructions were not offered yet at the time of the OPALS study. The total catchment population for the OPALS study is estimated at 2,500,000, with community sizes ranging from 15,605 to 774,072 (2001 Statistics Canada). The OPALS study database contains information prospectively collected following the Utstein style3 on more than 20,000 cardiac arrest cases.
Selection of participants We selected cases from the OPALS study database for which we had previously reported precise cardiac arrest location.5 These patients suffered out-of-hospital cardiac arrest of cardiac origin, not witnessed by EMS, between 1 January 1995 and 31 December 1999 (5-year period). In order to determine precise cardiac arrest location, we had linked the OPALS study database with the Ambulance Response Information System and the Municipal Property Assessment Corporation databases. Subsequently, we submitted cardiac arrest cases occurring in a private residential dwelling to the Municipal Property Assessment Corporation in order to obtain the residential property value for these locations. Because we used residential property value as a proxy for socioeconomic status, we excluded cardiac arrest cases occurring in public locations as well as those occurring in residential dwellings for which the value of an individual unit could not be determined (such as apartment buildings and condominiums). The majority of cardiac arrests occurred in private residential dwellings. The Ottawa Hospital Research Ethics Board reviewed and approved this study.
Methods of measurement for residential property values
Methods
We obtained the property value for all single residential dwellings from the Municipal Property Assessment Corporation. In April of 2006, the Municipal Property Assessment Corporation determined residential property value using a method called current value assessment. This method bases its evaluation on previous property sales in the community and up to 200 other factors. These factors include five key features such as location, lot dimension, living area, age of the property, and quality of construction. This technique of assessment is widely used in Canada and internationally in order to determine property taxes.
Study design
Outcome measures
We conducted a secondary analysis of data prospectively collected as part of the Ontario Prehospital Advanced Life Support (OPALS) study.
Bystander CPR rates ‘‘Bystander CPR’’ is an attempt at external chest compressions, with or without mouth-to-mouth ventilation,
Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims
419
performed by a person not part of an organized emergency response system.3 ‘‘Bystanders’’ may include physicians, nurses, off-duty paramedics and other medical personnel if they are not part of the dispatched emergency response team, but usually the term refers to a lay person who has witnessed the arrest. The presence of bystander CPR is documented by the paramedics on their ambulance call report, and was subsequently entered in the OPALS study database. Cardiac arrest survival We defined survival for out-of-hospital cardiac arrest as the return of spontaneous circulation followed by discharge of the patient from the hospital alive. This data was obtained as part of the OPALS study using a standardized review of hospital charts.20 Primary data analyses We report descriptive statistics with 95% confidence intervals, and performed stepwise logistic regression in order to quantify the effect of socioeconomic status on bystander CPR and survival rates for out-of-hospital cardiac arrest. We first performed univariate analyses to explore the effect of age, gender, witnessed status, time interval from 9-1-1 call to vehicle stopped at the scene, initial cardiac rhythm, city where cardiac arrest occurred, and property value on bystander CPR and survival rates. We only entered variables with a two-tailed level of significance of p ≤ 0.25 into the logistic regression models. We did not include the variable ‘‘initial cardiac rhythm’’ into the final model evaluating the adjusted effect of socioeconomic status on survival due to its association with many other variables entered in the model. This approach is consistent with that of others who consider initial cardiac rhythm as a dependant rather than an independent variable.21,22 We evaluated the fit of the final model using the Hosmer-Lemeshow goodness-of-fit statistics. We performed all analyses using the SAS statistical software Version 9.1 (Cary, NC, USA).
Table 1
Figure 1
Flow diagram of patient inclusion.
Results Characteristics of study subjects There were a total of 7707 out-of-hospital cardiac arrest cases of cardiac origin, not witnessed by EMS, between 1 January 1995 and 31 December 1999 in our 20 study communities. Among those, 3600 cases met all our inclusion criteria and 4107 did not (Figure 1 and Table 1). Excluded cases were of similar age and gender but, since they were more likely to experience cardiac arrest in a public location, were more
Patient and system characteristics for all victims of cardiac arrest over the 5-year period.
Characteristics
Included N = 3600
Excluded N = 4107
Mean age [range] Male gender (%) Witnessed arrest (%) Bystander CPR (%)
69.2 [16—100] 2550 (70.8) 1612 (44.7) 476 (13.2)
68.4 [16—102] 2763 (67.3) 2144 (52.2) 797 (19.4)
Initial cardiac arrest rhythm (%) Asystole VF/VT PEA
1566 (43.5) 1215 (33.8) 739 (20.5)
1578 (38.4) 1565 (38.1) 875 (21.3)
Mean time from call to vehicle stopa (min:s) Return to spontaneous circulation (%)
5:36 457 (12.7)
5:14 702 (17.0)
Discharged alive Overall (%) Witnessed cases in VF/VT (n = 782; %)
96 (2.7) 68 (8.7)
213 (5.2) 164(21.0)
Median property value (CAD$) [range]
184,000 [25,500—2,494,000]
—
a
Vehicle refers to first vehicle with defibrillator.
>$500,000 (N = 131)
71.6 58.0 46.6 16.8
31.3 22.9 44.3
5:54
13.7
1.5
71.1 64.2 39.9 12.8
29.7 24.3 43.2
5:42
11.5
2.0
C. Vaillancourt et al.
$400,000—500,000 (N = 148)
420
frequently witnessed, had slightly faster response times, and had better survival outcomes. Among included patients, overall survival to hospital discharge was low (2.7%). The median residential property value was $184,000, and ranged from $25,500 to $2,494,000. We also stratified the patient and system characteristics by residential property value categories of $100,000 to facilitate visual inspection of our data (Table 2). Cardiac arrest patients with higher residential property values were slightly older, received bystander CPR more frequently, experienced longer time intervals to arrival of first defibrillator, and had lower survival rates.
0.5
11.2
5:48
31.2 21.3 44.3
70.6 63.5 44.0 15.2
The results of the stepwise logistic regression analyses for influence socioeconomic status on bystander CPR and survival rates are presented in Tables 3 and 4. The adjusted odds ratio for the effect of property value per $100,000 on bystander CPR rate was 1.07 (95% CI 1.01—1.14; p = 0.03). The adjusted odds ratio for the effect of property value per $100,000 on survival to hospital discharge was 0.77 (95% CI 0.61—0.97; p = 0.03).
2.2 3.5 2.6
12.8 13.3 11.2
5:48 5:30 5:12
Mean time from call received to vehicle stop (min:s) Return to spontaneous circulation (%) Discharged alive (%)
35.9 21.0 40.0 31.3 17.2 50.1 Initial cardiac arrest rhythm (%) VF/VT PEA Asystole
34.3 20.4 43.6
68.0 73.6 40.5 12.3
69.0 68.0 44.9 12.9
69.1 68.9 47.3 12.9
Discussion
Mean age Male gender (%) Witnessed arrest (%) Bystander CPR (%)
$100,000—200,000 (N = 1695) <$100,000 (N = 383)
Property value (CAD$) Characteristics
Table 2
Patient and system characteristics stratified by property value categories.
$200,000—300,000 (N = 868)
$300,000—400,000 (N = 375)
Main results
This secondary data analysis was designed to analyze the effect of cardiac arrest victim’s socioeconomic status on their likelihood to receive bystander CPR or survive from out-of-hospital cardiac arrest. We used victim’s residential property value as a proxy for their socioeconomic status. We found an increased likelihood of bystander CPR with higher property values of cardiac arrest victims. At the same time, it appears that survival decreases as property values increase, even after adjusting for age and other factors. Our analyses included patients suffering cardiac arrest in the location of their private residence. This group represents the largest location-related proportion of cardiac arrest victims, and our analyses included a broad range of residential property values. We believe that public health agencies should implement CPR education strategies targeting lower socioeconomic groups, and attempt to determine the nature and quality of bystander CPR being performed in residential dwellings. We used residential property value as a proxy for socioeconomic status because neighborhood-based or aggregate measures of socioeconomic status do not account for individual socioeconomic status variability within a given area, and are not always predictive of a specific individual’s health outcomes.15 We know that socioeconomic status is a determinant of health outcomes and mortality13 and individual unit assessment levels, such as residential property value, are believed to accurately reflect the socioeconomic status of the inhabitants of the property.23 The British government uses council tax valuation bands, which are based on the categorization of property values, to determine the amount of council tax to be paid by property owners. Income, education, and occupation are traditionally used to classify socioeconomic status, but council tax valuation bands proved to be a useful substitution for these traditional socioeconomic status measures.24 Council tax valuation
Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims
421
Table 3 Logistic regression analysis evaluating the independent relationship of patient, EMS, and property value characteristics on bystander CPR rates. Covariate
Coefficient
Adjusted OR
95% CI
p-Value
Intercept Age EMS call to vehicle stop (per min) Witnessed arrest
−2.1143 −0.0101 0.0563 0.6388
0.99 1.06 1.89
0.98—1.00 1.00—1.12 1.44—2.49
0.04 0.06 <0.0001
Cardiac arrest rhythm VF/VT vs. asystole PEA vs. asystole
0.3738 −0.0762
1.45 0.93
0.71—2.98 0.44—1.94
0.005 0.31 0.84
0.0695
1.07
1.01—1.14
0.03
Property value (per $100,000) Hosmer and Lemeshow goodness-of-fit p = 0.81.
bands are inversely correlated with patient visits, health care costs24 , and mortality.23 Other investigators have used residential property value to estimate individual socioeconomic status.18,25 It is a valid proxy for socioeconomic status, and is correlated with previous measures of socioeconomic status such as median income per household.25 Thus, residential property value is a suitable measure to evaluate the effect of socioeconomic status on out-of-hospital cardiac arrest outcomes. This study is the first to show that bystander CPR rates were higher among victims with higher socioeconomic status. Another study found that bystanders who completed a level of education higher than high school were more likely to perform CPR.26 It is possible that families with a higher socioeconomic status have a higher level of education, are more knowledgeable about the signs and symptoms of a cardiac arrest, and are more likely to recognize the condition and initiate CPR. Although willingness to perform CPR does not seem to differ among people with different socioeconomic status,27 those with a higher socioeconomic status may have better access to CPR training. That being said, bystander CPR was not associated with increased survival for the cohort of cardiac arrest victims we analyzed. The effect of bystander CPR on survival was adjusted for the victim’s age, EMS time response, witnessed status, and socioeconomic status. This is in contrast with the findings of the OPALS study that a victim is much more likely to survive when receiving bystander CPR (OR 3.7 95% CI 2.5—5.4).9 Contrarily to the OPALS study, which analyzed the effect of bystander CPR for the whole cohort of cardiac arrest patients, we limited our subgroup analysis to victims collapsing at home.
Since the observed survival rate for home cardiac arrest is so small, it is possible that bystander CPR is unlikely to be able to demonstrate a benefit. In addition, victims collapsing at home are much more likely to be witnessed by a spouse of similar age, it is possible that the depth of chest compressions and overall CPR quality may differ from that being performed by a younger, stronger bystander in a public place.28 We also observed that survival rates were lower among victims with higher socioeconomic status. This is perhaps because of the very small survival rate observed in our population, and the resulting difficulty in adequately reflecting the impact of small changes in socioeconomic status on survival outcomes. Our findings are in contrast with a published abstract showing no association between a neighborhoodbased measure of socioeconomic status and cardiac arrest survival.17 Two other studies showed a positive correlation between socioeconomic status and survival.18,25 The study by Hallstrom was limited to 253 patients with an initial rhythm of ventricular fibrillation.25 The study by Clarke had a recruitment strategy comparable to ours, but less than half the patients included in our study.18 We adjusted the effect of socioeconomic status on survival for the victim’s age, EMS time intervals, witnessed status, and bystander CPR rate. Although advanced care paramedics became available in our study communities in February 2008, their presence did not influence survival outcomes in the OPALS study.9 There may be additional factors associated with socioeconomic status having an influence on cardiac arrest survival. One would expect that individuals with a higher socioeconomic status would be healthier and have a higher life expectancy. While
Table 4 Logistic regression analysis evaluating the independent relationship of patient, EMS, and property value characteristics on cardiac arrest survival to hospital discharge. Covariate
Coefficient
Adjusted OR
95% CI
p-Value
Intercept Age EMS call to vehicle stop (per min) Witnessed arrest Bystander CPR Property value (per $100,000)
−1.0379 −0.0252 −0.3351 1.7181 0.2790 −0.2614
0.98 0.72 5.57 1.32 0.77
0.96—0.99 0.63—0.82 3.34—9.31 0.78—2.24 0.61—0.97
0.0008 <0.0001 <0.0001 0.30 0.03
Hosmer and Lemeshow goodness-of-fit p = 0.48.
422 the incidence of cardiovascular disease and cardiac arrest may be lower among a population with higher socioeconomic status,11—14 those who nonetheless suffer a cardiac arrest may share the same fate as their lower socioeconomic status counterpart. Our study has many strong qualities. It is the largest study evaluating the association between socioeconomic status and cardiac arrest survival, and the first one to describe an association between socioeconomic status and bystander CPR rate. We performed a secondary data analysis of information collected prospectively as part of the OPALS study, which utilised a strong study design, and a rigorous data collection method.20 Patients included in our analyses come from a large number of urban and sub-urban communities, increasing the generalizability of our findings. We meticulously determined the precise cardiac arrest location of all cardiac arrest victims,5 and used a Government agency with high methodology standards to determine the individual property value of single residences included in our analyses. Our study contains several potential limitations. First, our study population originated from the OPALS database which encompassed 20 urban and sub-urban communities across Ontario. Residential property values could vary between regions such that a larger expensive property in a sub-urban community may equate to only a modest residence in an urban downtown centre. It may have been preferable to categorize property values by community percentile which would take into account the variability of property values within different communities. Although property values may be lower in a sub-urban location, an individual of higher socioeconomic status is still more likely to live in a more expensive house in that community. Moreover, while the size and quality of similarly valued properties may vary from one community to another, we believe it is the property value that is associated with socioeconomic status rather than the size of the property. Although the distribution of property values was skewed by some very expensive homes, most property values tended to be clustered between $100,000 and $200,000, and our sample included some very inexpensive houses as well. Second, we only looked at cardiac arrest cases occurring in single residential dwellings. It may be argued that this did not take into account the lower value residential units such as town homes and apartment buildings, but our cohort included houses with values as low as $25,500. We also did not take into account arrests that occurred in a public location. Our findings should not be extrapolated to cardiac arrest victims occurring in a location other than a single residential dwelling. However, since the majority of cardiac arrest cases take place in the victim’s own residence, we believe that the 3600 arrests which occurred in a single residential dwelling was representative of the largest proportion of out-of-hospital cardiac arrests. Third, since this was a secondary data analysis, there was a time of up to 11 years between the date of arrest and the property evaluation of arrest location. Over this time, with economic inflation, property values may have risen while individual purchasing power may not have followed at the same rate. Because of this, the current property value may not be entirely reflective of the victim’s socioeconomic status at the time of arrest. While this may change the mag-
C. Vaillancourt et al. nitude of our estimation of a victim’s socioeconomic status, this should not have affected their rank within the cohort. Finally, the socioeconomic status of an individual living in a given location can vary depending on whether the dwelling was inherited, is rented, or is associated with a large mortgage. However, property owners are still required to pay for the cost of living in a given residence, which may still be a good reflection of their socioeconomic status. It is also possible that the cardiac arrest victim in a given location may not have been the property owner, but rather a parent, a visitor, or an employee. We believe this situation occurs rarely and does not constitute a threat to the overall validity of our results. Our socioeconomic status proxy did not take into account the victim’s marital status or the number of people living in a given dwelling, all of which could have influenced the likelihood of receiving bystander CPR.
Conclusions This is the largest study evaluating the association between socioeconomic status and cardiac arrest survival, and the first one to describe an association between socioeconomic status and bystander CPR rate. For each $100,000 increment in residential property value, we observed an increase in bystander CPR rate and a decrease in survival for out-ofhospital cardiac arrest victims.
Conflict of interest None.
Acknowledgements We would like to acknowledge the Ontario Prehospital Advanced Life Support (OPALS) Study personnel for their unconditional help and support of this project as well as all paramedics looking after cardiac arrest victims in the OPALS communities. Funding: This project received funding from the Ottawa Hospital Department of Emergency Medicine Academic Practice Plan, University of Ottawa. Dr. Vaillancourt receives salary support from the Ottawa Health Research Institute and the Ottawa Hospital Department of Emergency Medicine Academic Practice Plan. Andre Lui received salary support from the University of Ottawa summer research program, and the Ottawa Hospital Department of Emergency Medicine Academic Practice Plan.
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16. Chu K, Swor R, Jackson R, et al. Race and survival after outof-hospital cardiac arrest in a suburban community. Ann Emerg Med 1998;31(4):478—82. 17. Denny C, Schull M, Szalai J, Stiell I. Socioeconomic status and survival after prehospital cardiac arrest. Published in abstract. Acad Emerg Med 2004;11(5):590—1. 18. Clarke SO, Schellenbaum GD, Rea TD. Socioeconomic status and survival from out-of-hospital cardiac arrest. Acad Emerg Med 2005;12(10):941—7. 19. Sayegh AJ, Swor R, Chu KH, et al. Does race or socioeconomic status predict adverse outcome after out of hospital cardiac arrest: a multi-center study. Resuscitation 1999;40(3):141—6. 20. Stiell IG, Wells GA, Spaite DW, et al. The Ontario Prehospital Advanced Life Support (OPALS) Study: rationale and methodology for cardiac arrest patients. Ann Emerg Med 1998;32(2): 180—90. 21. Wilcox-Gok VL. Survival from out-of-hospital cardiac arrest. A multivariate analysis. Med Care 1991;29(2):104—14. 22. Cummins RO, Eisenberg MS, Hallstrom AP, Litwin PE. Survival of out-of-hospital cardiac arrest with early initiation of cardiopulmonary resuscitation. Am J Emerg Med 1985;3(2):114—9. 23. Beale NR, Taylor GJ, Straker-Cook DMK. Is council tax valuation band a predictor of mortality? BMC Public Health 2002;2:17. 24. Fone DL, Dunstan F, Christie S, et al. Council tax valuation bands, socio-economic status and health outcome: a crosssectional analysis from the Caerphilly Health and Social Needs Study. BMC Public Health 2006;6:115. 25. Hallstrom A, Boutin P, Cobb L, Johnson E. Socioeconomic status and prediction of ventricular fibrillation survival. Am J Public Health 1993;83(2):245—8. 26. Swor R, Khan I, Domeier R, Honeycutt L, Chu K, Compton S. CPR training and CPR performance: do CPR-trained bystanders perform CPR? Acad Emerg Med 2006;13(6):596—601. 27. Brookoff D, Kellermann AL, Hackman BB, Somes G, Dobyns P. Do blacks get bystander cardiopulmonary resuscitation as often as whites? Ann Emerg Med 1994;24(6):1147—50. 28. Gallagher EJ, Lombardi G, Gennis P. Effectiveness of bystander cardiopulmonary resuscitation and survival following out-ofhospital cardiac arrest. JAMA 1995;274(24):1922—5.
available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/resuscitation
Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims夽 C. Vaillancourt a,b,∗, A. Lui a, V.J. De Maio d, G.A. Wells a,c, I.G. Stiell a,b a
Ottawa Health Research Institute, University of Ottawa, Ottawa, Ontario, Canada Department of Emergency Medicine, University of Ottawa, Ottawa, Ontario, Canada c Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada d Emergency Services Institute, WakeMed Health and Hospitals, Raleigh, NC, USA b
Received 1 March 2008; received in revised form 1 July 2008; accepted 17 July 2008
KEYWORDS Heart arrest; Asystole; Sudden cardiac death; Resuscitation; Socioeconomic factors; Social class
Summary Objectives: While lower socioeconomic status is associated with lower level of education and increased incidence of cardiovascular diseases, the impact of socioeconomic status on out-ofhospital cardiac arrest outcomes is unclear. We used residential property values as a proxy for socioeconomic status to determine if there was an association with: (1) bystander CPR rates and (2) survival to hospital discharge for out-of-hospital cardiac arrest. Methods: We performed a secondary data analysis of cardiac arrest cases prospectively collected as part of the Ontario Prehospital Advanced Life Support study, conducted in 20 cities with ALS and BLS-D paramedics. We measured patient and system characteristics for cardiac arrests of cardiac origin, not witnessed by EMS, occurring in a single residential dwelling. We obtained property values from the Municipal Property Assessment Corporation. Analyses included descriptive statistics with 95% CIs and stepwise logistic regression. Results: Three thousand six hundred cardiac arrest cases met our inclusion criteria between 1 January 1995 and 31 December 1999. Patient characteristics were: mean age 69.2, male 67.8%, witnessed 44.7%, bystander CPR 13.2%, VF/VT 33.8%, time to vehicle stop 5:36 min:s, return of spontaneous circulation 12.7%, and survival 2.7%. Median property value was $184,000 (range $25,500—2,494,000). For each $100,000 increment in property value, the likelihood of receiving bystander CPR increased (OR = 1.07; 95% CI 1.01—1.14; p = 0.03) and survival decreased (OR = 0.77; 95% CI 0.61—0.97; p = 0.03). Conclusions: This is the largest study showing an association between socioeconomic status and survival, and the first study showing an association with bystander CPR. Our findings suggest targeting CPR training among lower socioeconomic groups. © 2008 Elsevier Ireland Ltd. All rights reserved.
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at doi:10.1016/j.resuscitation.2008.07.012. ∗ Corresponding author. Tel.: +1 613 798 5555x17012; fax: +1 613 761 5351. E-mail address: [email protected] (C. Vaillancourt).
0300-9572/$ — see front matter © 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.resuscitation.2008.07.012
418
C. Vaillancourt et al.
Introduction
Setting
Cardiovascular disease is the leading cause of mortality in North America, and results in almost 700,000 deaths annually in the United States.1 More than 50% of all cardiovascular disease deaths are caused by sudden cardiac arrest,2 defined as the cessation of cardiac mechanical activity resulting in the absence of vital signs.3 Cardiac arrest is the first manifestation of cardiovascular disease in over 40% of victims.4 A typical victim is a male in his sixties, and 85% of outof-hospital cardiac arrests occur in private residences.5,6 The survival rate from out-of-hospital cardiac arrest rarely exceeds 5%.7 Those who survive maintain a level of functioning similar to that of a similar age group in the general population.8 Patient age, gender, initial cardiac rhythm, bystander CPR and early defibrillation are all factors known to influence outcomes for cardiac arrest patients.9 In addition to those factors, a victim’s socioeconomic status may also influence outcomes for out-of-hospital cardiac arrest.10 Socioeconomic status is a measure of an individual’s place within a social group based on various factors, including income and education. We know that risk factors for cardiovascular disease are more prevalent among individuals with lower socioeconomic status.11 Consequently, the incidence of coronary artery disease,12 death due to myocardial infarction,13 and sudden cardiac arrest14 is also higher among these individuals. In addition, longer delays in accessing emergency medical services (EMSs) care for chest pain have been observed in lower socioeconomic status neighborhoods,15 and lower bystander CPR rates have been observed in neighborhoods of different ethnic background.16 That being said, recent studies failed to show an association between an aggregate measure of socioeconomic status (median neighborhood income), and survival to hospital discharge for out-of-hospital cardiac arrest.17—19 Because socioeconomic status can vary greatly among individuals living within a given neighborhood, we believe an individual measure of socioeconomic status (residential property value) may better reflect the influence of socioeconomic status on out-of-hospital cardiac arrest outcomes. While lower socioeconomic status is associated with lower level of education and increased incidence of cardiovascular diseases, the impact of socioeconomic status on out-of-hospital cardiac arrest outcomes is unclear. The overall purpose of this study is to better understand the influence of socioeconomic status on out-of-hospital cardiac arrest outcomes. More specifically, we will use the patient’s residential property value as a proxy for their socioeconomic status to determine: (1) the association between socioeconomic status and bystander CPR rates and (2) The association between socioeconomic status and survival for out-of-hospital cardiac arrest.
The OPALS study was designed to evaluate the sequential survival benefit of implementing an early defibrillation program followed by advanced life support for out-of-hospital cardiac arrest patients. The OPALS study took place in 20 cities equipped with basic life support-defibrillation (BLS-D) and advanced care paramedics. 9-1-1 dispatch-assisted CPR instructions were not offered yet at the time of the OPALS study. The total catchment population for the OPALS study is estimated at 2,500,000, with community sizes ranging from 15,605 to 774,072 (2001 Statistics Canada). The OPALS study database contains information prospectively collected following the Utstein style3 on more than 20,000 cardiac arrest cases.
Selection of participants We selected cases from the OPALS study database for which we had previously reported precise cardiac arrest location.5 These patients suffered out-of-hospital cardiac arrest of cardiac origin, not witnessed by EMS, between 1 January 1995 and 31 December 1999 (5-year period). In order to determine precise cardiac arrest location, we had linked the OPALS study database with the Ambulance Response Information System and the Municipal Property Assessment Corporation databases. Subsequently, we submitted cardiac arrest cases occurring in a private residential dwelling to the Municipal Property Assessment Corporation in order to obtain the residential property value for these locations. Because we used residential property value as a proxy for socioeconomic status, we excluded cardiac arrest cases occurring in public locations as well as those occurring in residential dwellings for which the value of an individual unit could not be determined (such as apartment buildings and condominiums). The majority of cardiac arrests occurred in private residential dwellings. The Ottawa Hospital Research Ethics Board reviewed and approved this study.
Methods of measurement for residential property values
Methods
We obtained the property value for all single residential dwellings from the Municipal Property Assessment Corporation. In April of 2006, the Municipal Property Assessment Corporation determined residential property value using a method called current value assessment. This method bases its evaluation on previous property sales in the community and up to 200 other factors. These factors include five key features such as location, lot dimension, living area, age of the property, and quality of construction. This technique of assessment is widely used in Canada and internationally in order to determine property taxes.
Study design
Outcome measures
We conducted a secondary analysis of data prospectively collected as part of the Ontario Prehospital Advanced Life Support (OPALS) study.
Bystander CPR rates ‘‘Bystander CPR’’ is an attempt at external chest compressions, with or without mouth-to-mouth ventilation,
Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims
419
performed by a person not part of an organized emergency response system.3 ‘‘Bystanders’’ may include physicians, nurses, off-duty paramedics and other medical personnel if they are not part of the dispatched emergency response team, but usually the term refers to a lay person who has witnessed the arrest. The presence of bystander CPR is documented by the paramedics on their ambulance call report, and was subsequently entered in the OPALS study database. Cardiac arrest survival We defined survival for out-of-hospital cardiac arrest as the return of spontaneous circulation followed by discharge of the patient from the hospital alive. This data was obtained as part of the OPALS study using a standardized review of hospital charts.20 Primary data analyses We report descriptive statistics with 95% confidence intervals, and performed stepwise logistic regression in order to quantify the effect of socioeconomic status on bystander CPR and survival rates for out-of-hospital cardiac arrest. We first performed univariate analyses to explore the effect of age, gender, witnessed status, time interval from 9-1-1 call to vehicle stopped at the scene, initial cardiac rhythm, city where cardiac arrest occurred, and property value on bystander CPR and survival rates. We only entered variables with a two-tailed level of significance of p ≤ 0.25 into the logistic regression models. We did not include the variable ‘‘initial cardiac rhythm’’ into the final model evaluating the adjusted effect of socioeconomic status on survival due to its association with many other variables entered in the model. This approach is consistent with that of others who consider initial cardiac rhythm as a dependant rather than an independent variable.21,22 We evaluated the fit of the final model using the Hosmer-Lemeshow goodness-of-fit statistics. We performed all analyses using the SAS statistical software Version 9.1 (Cary, NC, USA).
Table 1
Figure 1
Flow diagram of patient inclusion.
Results Characteristics of study subjects There were a total of 7707 out-of-hospital cardiac arrest cases of cardiac origin, not witnessed by EMS, between 1 January 1995 and 31 December 1999 in our 20 study communities. Among those, 3600 cases met all our inclusion criteria and 4107 did not (Figure 1 and Table 1). Excluded cases were of similar age and gender but, since they were more likely to experience cardiac arrest in a public location, were more
Patient and system characteristics for all victims of cardiac arrest over the 5-year period.
Characteristics
Included N = 3600
Excluded N = 4107
Mean age [range] Male gender (%) Witnessed arrest (%) Bystander CPR (%)
69.2 [16—100] 2550 (70.8) 1612 (44.7) 476 (13.2)
68.4 [16—102] 2763 (67.3) 2144 (52.2) 797 (19.4)
Initial cardiac arrest rhythm (%) Asystole VF/VT PEA
1566 (43.5) 1215 (33.8) 739 (20.5)
1578 (38.4) 1565 (38.1) 875 (21.3)
Mean time from call to vehicle stopa (min:s) Return to spontaneous circulation (%)
5:36 457 (12.7)
5:14 702 (17.0)
Discharged alive Overall (%) Witnessed cases in VF/VT (n = 782; %)
96 (2.7) 68 (8.7)
213 (5.2) 164(21.0)
Median property value (CAD$) [range]
184,000 [25,500—2,494,000]
—
a
Vehicle refers to first vehicle with defibrillator.
>$500,000 (N = 131)
71.6 58.0 46.6 16.8
31.3 22.9 44.3
5:54
13.7
1.5
71.1 64.2 39.9 12.8
29.7 24.3 43.2
5:42
11.5
2.0
C. Vaillancourt et al.
$400,000—500,000 (N = 148)
420
frequently witnessed, had slightly faster response times, and had better survival outcomes. Among included patients, overall survival to hospital discharge was low (2.7%). The median residential property value was $184,000, and ranged from $25,500 to $2,494,000. We also stratified the patient and system characteristics by residential property value categories of $100,000 to facilitate visual inspection of our data (Table 2). Cardiac arrest patients with higher residential property values were slightly older, received bystander CPR more frequently, experienced longer time intervals to arrival of first defibrillator, and had lower survival rates.
0.5
11.2
5:48
31.2 21.3 44.3
70.6 63.5 44.0 15.2
The results of the stepwise logistic regression analyses for influence socioeconomic status on bystander CPR and survival rates are presented in Tables 3 and 4. The adjusted odds ratio for the effect of property value per $100,000 on bystander CPR rate was 1.07 (95% CI 1.01—1.14; p = 0.03). The adjusted odds ratio for the effect of property value per $100,000 on survival to hospital discharge was 0.77 (95% CI 0.61—0.97; p = 0.03).
2.2 3.5 2.6
12.8 13.3 11.2
5:48 5:30 5:12
Mean time from call received to vehicle stop (min:s) Return to spontaneous circulation (%) Discharged alive (%)
35.9 21.0 40.0 31.3 17.2 50.1 Initial cardiac arrest rhythm (%) VF/VT PEA Asystole
34.3 20.4 43.6
68.0 73.6 40.5 12.3
69.0 68.0 44.9 12.9
69.1 68.9 47.3 12.9
Discussion
Mean age Male gender (%) Witnessed arrest (%) Bystander CPR (%)
$100,000—200,000 (N = 1695) <$100,000 (N = 383)
Property value (CAD$) Characteristics
Table 2
Patient and system characteristics stratified by property value categories.
$200,000—300,000 (N = 868)
$300,000—400,000 (N = 375)
Main results
This secondary data analysis was designed to analyze the effect of cardiac arrest victim’s socioeconomic status on their likelihood to receive bystander CPR or survive from out-of-hospital cardiac arrest. We used victim’s residential property value as a proxy for their socioeconomic status. We found an increased likelihood of bystander CPR with higher property values of cardiac arrest victims. At the same time, it appears that survival decreases as property values increase, even after adjusting for age and other factors. Our analyses included patients suffering cardiac arrest in the location of their private residence. This group represents the largest location-related proportion of cardiac arrest victims, and our analyses included a broad range of residential property values. We believe that public health agencies should implement CPR education strategies targeting lower socioeconomic groups, and attempt to determine the nature and quality of bystander CPR being performed in residential dwellings. We used residential property value as a proxy for socioeconomic status because neighborhood-based or aggregate measures of socioeconomic status do not account for individual socioeconomic status variability within a given area, and are not always predictive of a specific individual’s health outcomes.15 We know that socioeconomic status is a determinant of health outcomes and mortality13 and individual unit assessment levels, such as residential property value, are believed to accurately reflect the socioeconomic status of the inhabitants of the property.23 The British government uses council tax valuation bands, which are based on the categorization of property values, to determine the amount of council tax to be paid by property owners. Income, education, and occupation are traditionally used to classify socioeconomic status, but council tax valuation bands proved to be a useful substitution for these traditional socioeconomic status measures.24 Council tax valuation
Socioeconomic status influences bystander CPR and survival rates for out-of-hospital cardiac arrest victims
421
Table 3 Logistic regression analysis evaluating the independent relationship of patient, EMS, and property value characteristics on bystander CPR rates. Covariate
Coefficient
Adjusted OR
95% CI
p-Value
Intercept Age EMS call to vehicle stop (per min) Witnessed arrest
−2.1143 −0.0101 0.0563 0.6388
0.99 1.06 1.89
0.98—1.00 1.00—1.12 1.44—2.49
0.04 0.06 <0.0001
Cardiac arrest rhythm VF/VT vs. asystole PEA vs. asystole
0.3738 −0.0762
1.45 0.93
0.71—2.98 0.44—1.94
0.005 0.31 0.84
0.0695
1.07
1.01—1.14
0.03
Property value (per $100,000) Hosmer and Lemeshow goodness-of-fit p = 0.81.
bands are inversely correlated with patient visits, health care costs24 , and mortality.23 Other investigators have used residential property value to estimate individual socioeconomic status.18,25 It is a valid proxy for socioeconomic status, and is correlated with previous measures of socioeconomic status such as median income per household.25 Thus, residential property value is a suitable measure to evaluate the effect of socioeconomic status on out-of-hospital cardiac arrest outcomes. This study is the first to show that bystander CPR rates were higher among victims with higher socioeconomic status. Another study found that bystanders who completed a level of education higher than high school were more likely to perform CPR.26 It is possible that families with a higher socioeconomic status have a higher level of education, are more knowledgeable about the signs and symptoms of a cardiac arrest, and are more likely to recognize the condition and initiate CPR. Although willingness to perform CPR does not seem to differ among people with different socioeconomic status,27 those with a higher socioeconomic status may have better access to CPR training. That being said, bystander CPR was not associated with increased survival for the cohort of cardiac arrest victims we analyzed. The effect of bystander CPR on survival was adjusted for the victim’s age, EMS time response, witnessed status, and socioeconomic status. This is in contrast with the findings of the OPALS study that a victim is much more likely to survive when receiving bystander CPR (OR 3.7 95% CI 2.5—5.4).9 Contrarily to the OPALS study, which analyzed the effect of bystander CPR for the whole cohort of cardiac arrest patients, we limited our subgroup analysis to victims collapsing at home.
Since the observed survival rate for home cardiac arrest is so small, it is possible that bystander CPR is unlikely to be able to demonstrate a benefit. In addition, victims collapsing at home are much more likely to be witnessed by a spouse of similar age, it is possible that the depth of chest compressions and overall CPR quality may differ from that being performed by a younger, stronger bystander in a public place.28 We also observed that survival rates were lower among victims with higher socioeconomic status. This is perhaps because of the very small survival rate observed in our population, and the resulting difficulty in adequately reflecting the impact of small changes in socioeconomic status on survival outcomes. Our findings are in contrast with a published abstract showing no association between a neighborhoodbased measure of socioeconomic status and cardiac arrest survival.17 Two other studies showed a positive correlation between socioeconomic status and survival.18,25 The study by Hallstrom was limited to 253 patients with an initial rhythm of ventricular fibrillation.25 The study by Clarke had a recruitment strategy comparable to ours, but less than half the patients included in our study.18 We adjusted the effect of socioeconomic status on survival for the victim’s age, EMS time intervals, witnessed status, and bystander CPR rate. Although advanced care paramedics became available in our study communities in February 2008, their presence did not influence survival outcomes in the OPALS study.9 There may be additional factors associated with socioeconomic status having an influence on cardiac arrest survival. One would expect that individuals with a higher socioeconomic status would be healthier and have a higher life expectancy. While
Table 4 Logistic regression analysis evaluating the independent relationship of patient, EMS, and property value characteristics on cardiac arrest survival to hospital discharge. Covariate
Coefficient
Adjusted OR
95% CI
p-Value
Intercept Age EMS call to vehicle stop (per min) Witnessed arrest Bystander CPR Property value (per $100,000)
−1.0379 −0.0252 −0.3351 1.7181 0.2790 −0.2614
0.98 0.72 5.57 1.32 0.77
0.96—0.99 0.63—0.82 3.34—9.31 0.78—2.24 0.61—0.97
0.0008 <0.0001 <0.0001 0.30 0.03
Hosmer and Lemeshow goodness-of-fit p = 0.48.
422 the incidence of cardiovascular disease and cardiac arrest may be lower among a population with higher socioeconomic status,11—14 those who nonetheless suffer a cardiac arrest may share the same fate as their lower socioeconomic status counterpart. Our study has many strong qualities. It is the largest study evaluating the association between socioeconomic status and cardiac arrest survival, and the first one to describe an association between socioeconomic status and bystander CPR rate. We performed a secondary data analysis of information collected prospectively as part of the OPALS study, which utilised a strong study design, and a rigorous data collection method.20 Patients included in our analyses come from a large number of urban and sub-urban communities, increasing the generalizability of our findings. We meticulously determined the precise cardiac arrest location of all cardiac arrest victims,5 and used a Government agency with high methodology standards to determine the individual property value of single residences included in our analyses. Our study contains several potential limitations. First, our study population originated from the OPALS database which encompassed 20 urban and sub-urban communities across Ontario. Residential property values could vary between regions such that a larger expensive property in a sub-urban community may equate to only a modest residence in an urban downtown centre. It may have been preferable to categorize property values by community percentile which would take into account the variability of property values within different communities. Although property values may be lower in a sub-urban location, an individual of higher socioeconomic status is still more likely to live in a more expensive house in that community. Moreover, while the size and quality of similarly valued properties may vary from one community to another, we believe it is the property value that is associated with socioeconomic status rather than the size of the property. Although the distribution of property values was skewed by some very expensive homes, most property values tended to be clustered between $100,000 and $200,000, and our sample included some very inexpensive houses as well. Second, we only looked at cardiac arrest cases occurring in single residential dwellings. It may be argued that this did not take into account the lower value residential units such as town homes and apartment buildings, but our cohort included houses with values as low as $25,500. We also did not take into account arrests that occurred in a public location. Our findings should not be extrapolated to cardiac arrest victims occurring in a location other than a single residential dwelling. However, since the majority of cardiac arrest cases take place in the victim’s own residence, we believe that the 3600 arrests which occurred in a single residential dwelling was representative of the largest proportion of out-of-hospital cardiac arrests. Third, since this was a secondary data analysis, there was a time of up to 11 years between the date of arrest and the property evaluation of arrest location. Over this time, with economic inflation, property values may have risen while individual purchasing power may not have followed at the same rate. Because of this, the current property value may not be entirely reflective of the victim’s socioeconomic status at the time of arrest. While this may change the mag-
C. Vaillancourt et al. nitude of our estimation of a victim’s socioeconomic status, this should not have affected their rank within the cohort. Finally, the socioeconomic status of an individual living in a given location can vary depending on whether the dwelling was inherited, is rented, or is associated with a large mortgage. However, property owners are still required to pay for the cost of living in a given residence, which may still be a good reflection of their socioeconomic status. It is also possible that the cardiac arrest victim in a given location may not have been the property owner, but rather a parent, a visitor, or an employee. We believe this situation occurs rarely and does not constitute a threat to the overall validity of our results. Our socioeconomic status proxy did not take into account the victim’s marital status or the number of people living in a given dwelling, all of which could have influenced the likelihood of receiving bystander CPR.
Conclusions This is the largest study evaluating the association between socioeconomic status and cardiac arrest survival, and the first one to describe an association between socioeconomic status and bystander CPR rate. For each $100,000 increment in residential property value, we observed an increase in bystander CPR rate and a decrease in survival for out-ofhospital cardiac arrest victims.
Conflict of interest None.
Acknowledgements We would like to acknowledge the Ontario Prehospital Advanced Life Support (OPALS) Study personnel for their unconditional help and support of this project as well as all paramedics looking after cardiac arrest victims in the OPALS communities. Funding: This project received funding from the Ottawa Hospital Department of Emergency Medicine Academic Practice Plan, University of Ottawa. Dr. Vaillancourt receives salary support from the Ottawa Health Research Institute and the Ottawa Hospital Department of Emergency Medicine Academic Practice Plan. Andre Lui received salary support from the University of Ottawa summer research program, and the Ottawa Hospital Department of Emergency Medicine Academic Practice Plan.
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