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Small-area analysis of social inequalities in residential exposure to road traffic noise in Marseilles, France

机译:法国马赛居民暴露于道路交通噪声中的社会不平等现象的小区域分析

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Background: Few studies have focused on the social inequalities associated with environmental noise despite its significant potential health effects. This study analysed the associations between area socio-economic status (SES) and potential residential exposure to road traffic noise at a small-area level in Marseilles, second largest city in France. Methods: We calculated two potential road noise exposure indicators (PNEI) at the census block level (for 24-h and night periods), with the noise propagation prediction model CadnaA. We built a deprivation index from census data to estimate SES at the census block level. Locally estimated scatterplot smoothing diagrams described the associations between this index and PNEIs. Since the extent to which coefficient values vary between standard regression models and spatial methods are sensitive to the specific spatial model, we analysed these associations further with various regression models controlling for spatial autocorrelation and conducted sensitivity analyses with different spatial weight matrices. Results: We observed a non-linear relation between the PNEIs and the deprivation index: exposure levels were highest in the intermediate categories. All the spatial models led to a better fit and more or less pronounced reductions of the regression coefficients; the shape of the relations nonetheless remained the same. Conclusion: Finding the highest noise exposure in midlevel deprivation areas was unexpected, given the general literature on environmental inequalities. It highlights the need to study the diversity of the patterns of environmental inequalities across various economic, social and cultural contexts. Comparative studies of environmental inequalities are needed, between regions and countries, for noise and other pollutants.
机译:背景:尽管有很大的潜在健康影响,但很少有研究关注与环境噪声相关的社会不平等。这项研究分析了法国第二大城市马赛地区社会经济地位(SES)与潜在居民在小面积水平道路交通噪声中的暴露之间的关联。方法:我们使用噪声传播预测模型CadnaA,在人口普查区级(24小时和夜间)计算了两个潜在的道路噪声暴露指标(PNEI)。我们根据普查数据建立了一个剥夺指数,以估算普查区一级的SES。局部估计的散点图平滑图描述了该索引与PNEI之间的关联。由于标准回归模型和空间方法之间的系数值变化程度对特定的空间模型敏感,因此我们使用控制空间自相关的各种回归模型进一步分析了这些关联,并使用不同的空间权重矩阵进行了敏感性分析。结果:我们观察到PNEI与剥夺指数之间存在非线性关系:中间类别中的暴露水平最高。所有的空间模型都导致更好的拟合,并且回归系数或多或少明显降低。关系的形状仍然保持不变。结论:鉴于有关环境不平等的一般文献,在中部贫困地区找到最高的噪声暴露是出乎意料的。它强调需要研究各种经济,社会和文化背景下环境不平等模式的多样性。需要对地区和国家之间的噪声和其他污染物进行环境不平等的比较研究。

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