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帕金森病的患病率与接近农业种植区的关系。

Parkinson's Disease Prevalence and Proximity to Agricultural Cultivated Fields.

机构信息

Clinical Research Center, Soroka University Medical Center, 84101 Beer Sheva, Israel ; Faculty of Health Sciences, Ben Gurion University, 84101 Beer Sheva, Israel.

Faculty of Health Sciences, Ben Gurion University, 84101 Beer Sheva, Israel ; Department of Neurology, Soroka University Medical Center, 84101 Beer Sheva, Israel.

出版信息

Parkinsons Dis. 2015;2015:576564. doi: 10.1155/2015/576564. Epub 2015 Aug 18.

Abstract

The risk for developing Parkinson's disease (PD) is a combination of multiple environmental and genetic factors. The Negev (Southern Israel) contains approximately 252.5 km(2) of agricultural cultivated fields (ACF). We aimed to estimate the prevalence and incidence of PD and to examine possible geographical clustering and associations with agricultural exposures. We screened all "Clalit" Health Services members in the Negev (70% of the population) between the years 2000 and 2012. Individual demographic, clinical, and medication prescription data were available. We used a refined medication tracer algorithm to identify PD patients. We used mixed Poisson models to calculate the smoothed standardized incidence rates (SIRs) for each locality. We identified ACF and calculate the size and distance of the fields from each locality. We identified 3,792 cases of PD. SIRs were higher than expected in Jewish rural localities (median SIR [95% CI]: 1.41 [1.28; 1.53] in 2001-2004, 1.62 [1.48; 1.76] in 2005-2008, and 1.57 [1.44; 1.80] in 2009-2012). Highest SIR was observed in localities located in proximity to large ACF (SIR 1.54, 95% CI 1.32; 1.79). In conclusion, in this population based study we found that PD SIRs were higher than expected in rural localities. Furthermore, it appears that proximity to ACF and the field size contribute to PD risk.

摘要

帕金森病(PD)的发病风险是多种环境和遗传因素共同作用的结果。内盖夫(以色列南部)大约有 252.5 平方公里的农业种植区(ACF)。我们旨在评估 PD 的患病率和发病率,并检查可能的地理聚集性和与农业暴露的关联。我们筛选了 2000 年至 2012 年间内盖夫地区的所有“Clalit”健康服务成员(占人口的 70%)。个体人口统计学、临床和药物处方数据均可获得。我们使用改良的药物示踪算法来识别 PD 患者。我们使用混合泊松模型计算每个地点的平滑标准化发病率(SIR)。我们确定了 ACF,并计算了每个地点与田地的大小和距离。我们共发现 3792 例 PD 病例。犹太农村地区的 SIR 高于预期(2001-2004 年中位数 SIR[95%CI]:1.41[1.28;1.53],2005-2008 年 1.62[1.48;1.76],2009-2012 年 1.57[1.44;1.80])。在靠近大型 ACF 的地区发现了最高的 SIR(SIR 1.54,95%CI 1.32;1.79)。总之,在这项基于人群的研究中,我们发现农村地区的 PD SIR 高于预期。此外,似乎接近 ACF 和农田面积会增加 PD 风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f4e/4556329/351cf1628f5e/PD2015-576564.001.jpg

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