Geographical Variation in Ambulance Calls Is Associated With Socioeconomic Status

Authors

  • Arul Earnest PhD, MSc, DLSHTM,

    1. From the Centre for Quantitative Medicine, Office of Clinical Sciences, Duke–National University Singapore Graduate Medical School (AE, SBT), Singapore; and the Department of Emergency Medicine, Singapore General Hospital (NS, MEHO), Singapore.
    Search for more papers by this author
  • Say Beng Tan PhD, MSc, CStat,

    1. From the Centre for Quantitative Medicine, Office of Clinical Sciences, Duke–National University Singapore Graduate Medical School (AE, SBT), Singapore; and the Department of Emergency Medicine, Singapore General Hospital (NS, MEHO), Singapore.
    Search for more papers by this author
  • Nur Shahidah,

    1. From the Centre for Quantitative Medicine, Office of Clinical Sciences, Duke–National University Singapore Graduate Medical School (AE, SBT), Singapore; and the Department of Emergency Medicine, Singapore General Hospital (NS, MEHO), Singapore.
    Search for more papers by this author
  • Marcus Eng Hock Ong MBBS (S’pore), MPH

    1. From the Centre for Quantitative Medicine, Office of Clinical Sciences, Duke–National University Singapore Graduate Medical School (AE, SBT), Singapore; and the Department of Emergency Medicine, Singapore General Hospital (NS, MEHO), Singapore.
    Search for more papers by this author

  • This study was supported by grants from the National Medical Research Council, Ministry of Health, Singapore (NMRC/0989/ 2005), as well as the Duke–National University Singapore Graduate Medical School SRP block grant.

  • The authors have no potential conflicts of interest to disclose.

  • Supervising Editor: David C. Cone, MD.

and reprints: Arul Earnest, PhD, MSc, DLSHTM; e-mail: arul.earnest@duke-nus.edu.sg.

Abstract

ACADEMIC EMERGENCY MEDICINE 2012; 19:180–188 © 2012 by the Society for Academic Emergency Medicine

Abstract

Objectives:  The main objective was to explore the relationship between socioeconomic status and the spatial distribution of ambulance calls, as modeled in the island nation of Singapore, at the Development Guide Plan (DGP) level (equivalent to census tracts in the United States).

Methods:  Ambulance call data came from a nationwide registry from January to May 2006. We used a conditional autoregressive (CAR) model to create smoothed maps of ambulance calls at the DGP level, as well as spatial regression models to evaluate the relationship between the risk of calls with regional measures of socioeconomic status, such as household type and both personal and household income.

Results:  There was geographical correlation in the ambulance calls, as well as a socioeconomic gradient in the relationship with ambulance calls of medical-related (but not trauma-related) reasons. For instance, the relative risk (RR) of medical ambulance calls decreased by a factor of 0.66 (95% credible interval [CrI] = 0.56 to 0.79) for every 10% increase in the proportion of those with monthly household income S$5000 and above. The top three DGPs with the highest risk of medical-related ambulance calls were Changi (RR = 29, 95% CrI = 24 to 35), downtown core (RR = 8, 95% CrI = 6 to 9), and Orchard (RR = 5, 95% CrI = 4 to 6).

Conclusions:  This study demonstrates the utility of geospatial analysis to relate population socioeconomic factors with ambulance call volumes. This can serve as a model for analysis of other public health systems.

Ancillary