不要相信现代环境流行病学家!

H. Ulmer
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摘要

在欧洲,空气污染每年导致40多万人过早死亡——因此,德国报纸和其他媒体于2020年9月9日向欧洲环境署(European Environment Agency)提出投诉[1]。如果你问这一具有严重政治和经济后果的声明的科学依据,你会发现多年来有大量的研究。几乎所有这些研究都描述了关于空气污染和区域发病率的“关联”、“相互作用”或模型计算,但对作者来说,没有令人信服的因果关系证据。相关性并不能证明因果关系的相互作用,它们包括一个高风险的鹳——统计数据。类似的情况也存在于氮氧化物的风险水平中,欧盟将其定为40 μg/m3(年平均值),以“保护人类健康和环境”[2]。在德国,根据全面的毒理学研究,在工作场所长期接触的mak值达到950 μg/m3(即高出23倍)。环境政治家对宣传这样的“坏消息”(欧洲每年有40万人死亡)和公共媒体喜欢这样的消息非常感兴趣。因此,针对这种情况,作者从德国卫生部得到了以下答复(2020年9月23日09:02):通常用于确认因果关系的毒理学和临床研究不适合回答此类问题(参考Bradfort Hill标准[3])。为什么生物流行病学家年复一年地从事这样的研究?也许政治和公众的关注保证了成功获得第三方资助和获得影响分数的良好机会,这在实际的科学业务中非常有利。因此,作者有兴趣讨论这些考虑因素,以获得新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Don’t trust the modern environmental epidemiologists!
Air pollution is responsible for more than 400.000 premature deaths/year in Europe – so German newspapers and other media complained at 9 September 2020, refering to the European Environment Agency [1]. If you ask the scientic base of this statement with severe political and economic consequences, you will find numerous studies since many years. Nearly all these studies describe “associations”, “interactions” ore model calculations regarding air pollution and regional incidences, but for the author not a convincing proof for causality. Correlations don’t proof causal interactions, they include a hight risk of stork- -statistics. A similar case exist in the risk-level of NOx, decided by the EU as 40 μg/m3 (mean of year) to “protect human health and the environment” [2]. In Germany the MAK-value amounts to 950 μg/m3 (i.e. 23 times higher) for longlife expositions at workplaces, based on thorough toxicologic studies. There is a high interest of environmental politicans to propagate such “bad news” (400.000 deaths/year in Europe) and the public media like such news. So the author, claming about this scenario, got the followimg answer from the German ministry of health (23 September 2020 09:02): Usual toxikologic and clinical studies, often used to confirm a causality, are not suitable answering such questiions (with reference to Bradfort Hill criteria [3]). Why biomatical epidemiologists work on year after year for such research? Perhaps political and public attention garantee good chances for successful third-party-funding and acquisition of impact scores, very favorable in the actual scientific business. So the author is interested to discuss these considerations for getting new insights.
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