Centre for Quantitative Medicine, Office of Clinical Sciences, Duke-National University Singapore Graduate Medical School, Singapore.
Acad Emerg Med. 2012 Feb;19(2):180-8. doi: 10.1111/j.1553-2712.2011.01280.x.
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).
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.
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).
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.
本研究旨在探索社会经济地位与救护车呼叫的空间分布之间的关系,以新加坡的发展指导规划(DGP)级别(相当于美国的人口普查区)作为模型。
救护车呼叫数据来自 2006 年 1 月至 5 月的全国登记处。我们使用条件自回归(CAR)模型在 DGP 级别创建救护车呼叫的平滑地图,并使用空间回归模型评估呼叫风险与区域社会经济地位指标(如家庭类型以及个人和家庭收入)之间的关系。
救护车呼叫存在地理相关性,并且与医疗相关(而非创伤相关)原因的救护车呼叫之间存在社会经济梯度。例如,对于每月家庭收入超过 5000 新元的人群比例每增加 10%,医疗救护车呼叫的相对风险(RR)降低 0.66(95%可信区间[CrI]为 0.56 至 0.79)。医疗相关救护车呼叫风险最高的前三个 DGP 是樟宜(RR=29,95%CrI=24 至 35)、市中心核心区(RR=8,95%CrI=6 至 9)和乌节路(RR=5,95%CrI=4 至 6)。
本研究表明,地理空间分析可用于将人口社会经济因素与救护车呼叫量联系起来。这可以作为分析其他公共卫生系统的模型。