Han Daikwon, Rogerson Peter A, Bonner Matthew R, Nie Jing, Vena John E, Muti Paola, Trevisan Maurizio, Freudenheim Jo L
Department of Social and Preventive Medicine, University at Buffalo, Buffalo, NY 14214 USA.
Int J Health Geogr. 2005 Apr 12;4(1):9. doi: 10.1186/1476-072X-4-9.
Most analyses of spatial clustering of disease have been based on either residence at the time of diagnosis or current residence. An underlying assumption in these analyses is that residence can be used as a proxy for environmental exposure. However, exposures earlier in life and not just those in the most recent period may be of significance. In breast cancer, there is accumulating evidence that early life exposures may contribute to risk. We explored spatio-temporal patterns of risk surfaces using data on lifetime residential history in a case control study of breast cancer, and identified elevated areas of risk and areas potentially having more exposure opportunities, defined as risk surfaces in this study. This approach may be more relevant in understanding the environmental etiology of breast cancer, since lifetime cumulative exposures or exposures at critical times may be more strongly associated with risk for breast cancer than exposures from the recent period. RESULTS: A GIS-based exploratory spatial analysis was applied, and spatio-temporal variability of those risk surfaces was evaluated using the standardized difference in density surfaces between cases and controls. The significance of the resulting risk surfaces was tested and reported as p-values. These surfaces were compared for premenopausal and postmenopausal women, and were obtained for each decade, from the 1940s to 1990s. We found strong evidence of clustering of lifetime residence for premenopausal women (for cases relative to controls), and a less strong suggestion of such clustering for postmenopausal women, and identified a substantial degree of temporal variability of the risk surfaces. CONCLUSION: We were able to pinpoint geographic areas with higher risk through exploratory spatial analyses, and to assess temporal variability of the risk surfaces, thus providing a working hypothesis on breast cancer and environmental exposures. Geographic areas with higher case densities need further epidemiologic investigation for potential relationships between lifetime environmental exposures and breast cancer risk. Examination of lifetime residential history provided additional information on geographic areas associated with higher risk; limiting exploration of chronic disease clustering to current residence may neglect important relationships between location and disease.
大多数疾病空间聚集性分析都是基于诊断时的居住地或当前居住地。这些分析的一个潜在假设是,居住地可作为环境暴露的替代指标。然而,生命早期的暴露而非仅最近时期的暴露可能具有重要意义。在乳腺癌方面,越来越多的证据表明生命早期暴露可能会增加患病风险。在一项乳腺癌病例对照研究中,我们利用终生居住史数据探索了风险面的时空模式,并确定了风险升高区域和潜在暴露机会更多的区域,本研究将其定义为风险面。这种方法可能在理解乳腺癌的环境病因方面更具相关性,因为终生累积暴露或关键时期的暴露可能比近期暴露与乳腺癌风险的关联更强。
应用了基于地理信息系统(GIS)的探索性空间分析,并使用病例与对照之间密度面的标准化差异评估了这些风险面的时空变异性。对所得风险面的显著性进行了检验,并报告为p值。比较了绝经前和绝经后女性的这些风险面,并获取了从20世纪40年代到90年代每十年的风险面。我们发现绝经前女性终生居住地存在明显的聚集证据(病例相对于对照),绝经后女性的这种聚集迹象较弱,并确定了风险面存在相当程度的时间变异性。
我们能够通过探索性空间分析确定风险较高的地理区域,并评估风险面的时间变异性,从而为乳腺癌与环境暴露提供一个可行的假设。病例密度较高的地理区域需要进一步进行流行病学调查,以研究终生环境暴露与乳腺癌风险之间的潜在关系。检查终生居住史提供了与较高风险相关的地理区域的额外信息;将慢性病聚集性的探索局限于当前居住地可能会忽略地点与疾病之间的重要关系。