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. 2011 Oct;58(4):343-51.
doi: 10.1016/j.annemergmed.2010.12.014. Epub 2011 Jan 15.

Spatial variation and geographic-demographic determinants of out-of-hospital cardiac arrests in the city-state of Singapore

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Spatial variation and geographic-demographic determinants of out-of-hospital cardiac arrests in the city-state of Singapore

Marcus Eng Hock Ong et al. Ann Emerg Med. 2011 Oct.

Abstract

Study objective: Our primary objective is to calculate the relative risk of cardiac arrests at the development guide plan (DGP) (equivalent to census tract) level in a city-state, Singapore, and examine its relationship with key area-level population characteristics.

Methods: This was an observational ecological study design. We calculated the relative risk as the ratio of the observed and population standardized expected counts of out-of-hospital cardiac arrests in Singapore, aggregated at DGP level. Data were collected from October 2001 to October 2004. We used conditional autoregressive spatial models to examine the predictors of increased risk at the DGP level.

Results: We found a spatial distribution of cardiac arrests, with an unexpected cluster caused by nonresident arrests occurring at the international airport. The risk of out-of-hospital cardiac arrest more than doubled, 2.35 (95% confidence interval [CI] 1.28 to 4.48), for each 5-point increase in the proportion of people aged 65 years and older. For each 5-point increase in the proportion of Chinese individuals living in a DGP, the risk of out-of-hospital cardiac arrest was reduced by a factor of 0.8 (95% CI 0.7 to 0.9). The risk of out-of-hospital cardiac arrest increased by 1.49-fold (95% CI 1.18 to 1.82) for every 5-point increase in the proportion of households with no family nucleus (live alone). When restricted to residential cases of out-of-hospital cardiac arrest, none of the variables remained significant, possibly because of small sample size.

Conclusion: The risk of cardiac arrests could be related to the age and racial and family structure of DGPs in Singapore. This article models how such data can help to direct public health education, cardiopulmonary resuscitation training, and public access defibrillation programs in other health systems.

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