Detecting spatiotemporal clusters of accidental poisoning mortality among Texas counties, U.S., 1980 - 2001.
Detecting spatiotemporal clusters of accidental poisoning mortality among Texas counties, U.S., 1980 - 2001.
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DOI：
10.1186/1476-072x-3-25
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发表时间：
2004-10-27
影响因子：
4.9
通讯作者：
Harris AM
中科院分区：
文献类型：
--
作者：
Nkhoma ET;Ed Hsu C;Hunt VI;Harris AM
在美国，意外中毒是仅次于机动车事故的主要伤害原因之一。根据疾病控制和预防中心的数据，在过去的14年里，全国意外中毒死亡率一直在上升。在德克萨斯州，意外中毒的死亡率反映了全国的趋势，从1981年到2001年呈线性增长。这项研究的目的是确定德克萨斯州各县之间是否存在意外中毒死亡的时空集群，如果是，是否根据性别和种族/民族在集群和风险方面存在差异。空间扫描统计结合地理信息系统软件用于识别1980-2001年间德克萨斯州各县之间的潜在聚集性，并使用泊松回归来评估风险差异。在德克萨斯州的不同地区确定了几个重要的(P<；0.05)意外中毒死亡集群。集群的地理和时间持久性因种族、性别和种族/性别组合的不同而不同，大多数集群持续到本十年。泊松回归显示，不同种族和性别的风险有显著差异。与其他种族/民族相比，黑人人群意外中毒死亡的风险最大(相对风险(RR)=1.25，95%可信区间(CI)=1.24~1.27)，而以女性人口为参照，男性人群意外中毒死亡风险较高(RR=2.47，95%CI=2.45~2.50)。本研究的结果为德克萨斯州意外中毒死亡集群的存在提供了证据，证明了这些集群在本十年中的持久性，并显示了意外中毒死亡风险和集群的时空变化，以及按性别和种族/民族划分的集群。通过量化不同地点、时间和人员的意外中毒死亡率差异，本研究展示了空间扫描统计与地理信息系统和回归方法相结合在确定公共卫生规划和资源分配的优先领域的有效性。
Accidental poisoning is one of the leading causes of injury in the United States, second only to motor vehicle accidents. According to the Centers for Disease Control and Prevention, the rates of accidental poisoning mortality have been increasing in the past fourteen years nationally. In Texas, mortality rates from accidental poisoning have mirrored national trends, increasing linearly from 1981 to 2001. The purpose of this study was to determine if there are spatiotemporal clusters of accidental poisoning mortality among Texas counties, and if so, whether there are variations in clustering and risk according to gender and race/ethnicity. The Spatial Scan Statistic in combination with GIS software was used to identify potential clusters between 1980 and 2001 among Texas counties, and Poisson regression was used to evaluate risk differences. Several significant (p < 0.05) accidental poisoning mortality clusters were identified in different regions of Texas. The geographic and temporal persistence of clusters was found to vary by racial group, gender, and race/gender combinations, and most of the clusters persisted into the present decade. Poisson regression revealed significant differences in risk according to race and gender. The Black population was found to be at greatest risk of accidental poisoning mortality relative to other race/ethnic groups (Relative Risk (RR) = 1.25, 95% Confidence Interval (CI) = 1.24 – 1.27), and the male population was found to be at elevated risk (RR = 2.47, 95% CI = 2.45 – 2.50) when the female population was used as a reference. The findings of the present study provide evidence for the existence of accidental poisoning mortality clusters in Texas, demonstrate the persistence of these clusters into the present decade, and show the spatiotemporal variations in risk and clustering of accidental poisoning deaths by gender and race/ethnicity. By quantifying disparities in accidental poisoning mortality by place, time and person, this study demonstrates the utility of the spatial scan statistic combined with GIS and regression methods in identifying priority areas for public health planning and resource allocation.