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意大利皮埃蒙特的肌萎缩侧索硬化症:发病病例的贝叶斯空间分析。

Amyotrophic lateral sclerosis in Piedmont (Italy): a Bayesian spatial analysis of the incident cases.

机构信息

Department of Public Health and Microbiology, University of Turin, Turin, Italy.

出版信息

Amyotroph Lateral Scler Frontotemporal Degener. 2013 Jan;14(1):58-65. doi: 10.3109/21678421.2012.733401. Epub 2012 Oct 22.

Abstract

In the analysis of risk factors in amyotrophic lateral sclerosis (ALS), few ecological studies, based on the relationship between the distribution of the patients in a given area and the environmental exposures, have been performed. The aim of our study was to depict the spatial risk distribution of ALS in Piedmont's resident population during the period 1995-2004. Data were collected from the Piedmont and Aosta Valley Register for ALS, which is a prospective epidemiological archive for gathering all the ALS incident cases in north-western Italy. Only cases from Piedmont were considered. The Besag, York and Molliè model was used to estimate smoothed standardized incidence ratios (SIR) by municipalities either overall or stratified by gender and age class. Results demonstrated that excess of risk was particularly evident in the area of Cuneo, Alessandria and Vercelli (SIR > 1.2). The results were evident for both genders, but in particular for males aged 35-60 years. Given the geographic distribution of rural areas, our results suggest that the environmental exposure to agricultural chemicals could be possibly linked to this pattern. Despite some limits of the spatial analysis in the study of rare diseases, results appear coherent with literature data, stimulating other in-depth analysis in this field of research.

摘要

在肌萎缩侧索硬化症 (ALS) 的危险因素分析中,很少有基于特定地区患者分布与环境暴露之间关系的生态学研究。我们的研究旨在描述 1995-2004 年间皮埃蒙特居民中 ALS 的空间风险分布。数据来自皮埃蒙特和奥斯塔谷 ALS 登记处,这是一个前瞻性的流行病学档案,用于收集意大利西北部所有的 ALS 发病病例。仅考虑来自皮埃蒙特的病例。采用 Besag、York 和 Molliè 模型,按市镇对总人群或按性别和年龄组进行分层,估计标准化发病比 (SIR) 的平滑值。结果表明,库内奥、亚历山德里亚和韦尔切利地区的风险明显过高 (SIR>1.2)。这些结果在男女中均明显,但在 35-60 岁的男性中更为明显。鉴于农村地区的地理分布,我们的结果表明,接触农业化学品的环境暴露可能与此模式有关。尽管在研究罕见疾病时空间分析存在一些限制,但结果与文献数据一致,激发了该研究领域的其他深入分析。

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