Unit of Epidemiology and Medical Statistics, Department of Public Health and Community Medicine, University of Verona, Verona, Italy.
Sci Total Environ. 2012 Jan 1;414:380-6. doi: 10.1016/j.scitotenv.2011.10.020. Epub 2011 Nov 17.
When pollution data from a monitoring network is not available, mapping the spatial distribution of disease can be useful to identify populations at risk and to suggest a potential role for suspected emission sources. We aimed at obtaining a continuous spatial representation of the prevalence of symptoms that are potentially associated with the exposure to the pollutants emitted from the wood factories in the children who live in the district of Viadana (Northern Italy).
In 2006, all the parents of the children aged 3-14 years residing in the Viadana district (n = 3854), filled in a questionnaire on respiratory symptoms, irritation symptoms of the eyes and skin, use of health services. The children's residential addresses were also collected and geocoded. Generalized additive models and local weighted regression (LOWESS) were used to estimate the distribution of the symptoms, to test for spatial trends of the symptoms' prevalence and to control for potential confounders. Permutation tests were used to identify the areas of significantly increased risk ("hot spots").
The prevalence of respiratory symptoms, eye symptoms and the use of health services showed a statistically significant spatial variation (p < 0.05), but skin symptoms did not. Symptoms' prevalence was lower in the northern part of the district, where no wood factories were present, and it was higher in the southern part, where the two big chipboard industries were located. Hot spots were identified fairly near to one of the two chipboard industries in the district.
The north-to-south trend in the prevalence of respiratory and eye symptoms, but not of skin symptoms, as well as the location of hot spots, are consistent with the potential exposure to air pollutants both emitted by the wood factories and related to traffic. In these "high risk areas" monitoring of pollution and preventive actions are clearly needed.
当监测网络中的污染数据不可用时，绘制疾病的空间分布有助于识别处于风险中的人群，并提示疑似排放源的潜在作用。我们旨在获得与居住在维亚达纳（意大利北部）地区的儿童接触来自木材厂排放的污染物相关的症状流行的连续空间表示。
2006 年，居住在维亚达纳地区的所有 3-14 岁儿童的父母（n=3854）填写了一份关于呼吸症状、眼睛和皮肤刺激症状、使用卫生服务的问卷。还收集了儿童的居住地址并进行了地理编码。使用广义加性模型和局部加权回归（LOWESS）来估计症状的分布，检验症状流行的空间趋势，并控制潜在的混杂因素。置换检验用于识别风险显著增加的区域（“热点”）。
呼吸症状、眼睛症状和卫生服务的使用的流行率表现出统计学上的显著空间变化（p<0.05），但皮肤症状没有。在该地区北部没有木材厂的地方，症状流行率较低，而在南部有两个大型刨花板工业的地方，症状流行率较高。在该地区的两个刨花板厂附近确定了热点。
呼吸和眼睛症状流行率从北到南的趋势，但皮肤症状没有，以及热点的位置，与木材厂排放的空气污染物以及与交通相关的潜在暴露一致。在这些“高风险区域”，需要对污染进行监测并采取预防措施。
