Things that apparently cause cancer

那些“显然”会导致癌症的事物

It would shock you to know that Costco, according to a new Harvard School of Public Health methodology, caused 120,687 cases of cancer mortality nationally every year, simply due to living in close proximity to their warehouses. Private colleges accounted for 83,782 more. Harvard itself is responsible for 5,842 cancer deaths. Living near a Major League Baseball field causes almost 19 times as many cancer deaths as living near a Major League Soccer pitch. These conclusions are obviously absurd, but they come from the exact same methodology that researchers at Harvard use to “prove” that nuclear power plants cause cancer in nearby communities.

如果你知道根据哈佛大学公共卫生学院的一项新方法论，Costco（好市多）每年在全国范围内导致了 120,687 例癌症死亡，仅仅是因为人们居住在离其仓库较近的地方，你一定会感到震惊。私立大学导致了另外 83,782 例死亡。哈佛大学本身就造成了 5,842 例癌症死亡。居住在职业棒球大联盟（MLB）球场附近导致的癌症死亡人数，几乎是居住在职业足球大联盟（MLS）球场附近的 19 倍。这些结论显然是荒谬的，但它们却出自哈佛大学研究人员用来“证明”核电站会导致周边社区癌症的同一套方法论。

Earlier this year, Adam Stein and I called out a series of Harvard studies showing that nuclear power plants were associated with higher rates of cancer incidence and cancer mortality as nonsense. Now that we’ve spent the last few months replicating the analysis and expanding it, we are able to show that no matter what landmark you use, their methodology will show an increased cancer risk and mortality. The studies simply do not prove anything about cancer incidence.

今年早些时候，亚当·斯坦（Adam Stein）和我指出，哈佛大学一系列声称核电站与癌症发病率和死亡率升高有关的研究纯属无稽之谈。在过去几个月里，我们对这些分析进行了复现和扩展，结果表明，无论你使用什么地标作为变量，他们的方法论都会显示出癌症风险和死亡率的增加。这些研究根本无法证明任何关于癌症发病率的结论。

Let’s recap: In December 2025, researchers led by Yazan Alwadi at Harvard’s T.H. Chan School of Public Health published a paper in Environmental Health that claimed to find that cancer incidence increased for people living closer to nuclear power plants in Massachusetts. In March, the same researchers published an expanded nationwide study claiming a similar result—this time looking at cancer mortality rates, rather than incidence—in Nature Communications. This was followed by a paper in the Journal of Exposure Science & Environmental Epidemiology that looked at associations of lung, breast, and colon cancers. Most recently, a study of total mortality, not just cancer, was published in the European journal Environmental Epidemiology.

回顾一下：2025 年 12 月，哈佛大学陈曾熙公共卫生学院的亚赞·阿尔瓦迪（Yazan Alwadi）领导的研究团队在《环境健康》（Environmental Health）杂志上发表了一篇论文，声称发现居住在马萨诸塞州核电站附近的人群癌症发病率有所上升。今年 3 月，同一研究团队在《自然-通讯》（Nature Communications）上发表了一项扩展的全国性研究，声称得出了类似的结果——这次关注的是癌症死亡率而非发病率。随后，《暴露科学与环境流行病学杂志》（Journal of Exposure Science & Environmental Epidemiology）发表了一篇论文，探讨了肺癌、乳腺癌和结肠癌的相关性。最近，欧洲期刊《环境流行病学》（Environmental Epidemiology）发表了一项关于总死亡率（不仅仅是癌症）的研究。

The papers construct a “proximity score” based on distance from nuclear plants, up to 120 km in Massachusetts and 200 km in the national studies (about 75 and 125 miles). Every ZIP code or county inside those radii is treated as exposed, with closer locations receiving higher weights. If a ZIP code or county is within range of multiple sites, then the effect is cumulative. That means that a county that is in close proximity to one nuclear power plant could have a smaller score than another county that is further away from any one power plant but within range of many.

这些论文基于与核电站的距离构建了一个“邻近度评分”，在马萨诸塞州的研究中距离上限为 120 公里，在全国性研究中为 200 公里（约 75 英里和 125 英里）。这些半径内的每个邮政编码区或县都被视为“暴露区”，距离越近权重越高。如果某个邮政编码区或县处于多个核电站的范围内，其影响则是累加的。这意味着，一个紧邻一座核电站的县，其评分可能反而低于另一个距离任何单一核电站较远、但处于多个核电站辐射范围内的县。

From this proximity score, the authors run regressions testing the outcome (cancer incidence, cancer mortality, or total mortality) on the proximity of the county and a collection of covariates. From this, they use the statistical coefficients, construct the Relative Risk for each county, age, and sex group, and compute the Attributable Fraction, from which they derive the number of attributed deaths from the nuclear power plant from 2000 to 2018. The authors state that their methodology and results provide the scientific basis and public health justification for an expanded research program.

基于这个邻近度评分，作者运行回归分析，测试结果（癌症发病率、癌症死亡率或总死亡率）与县域邻近度及一系列协变量之间的关系。由此，他们利用统计系数构建了每个县、年龄和性别组的相对风险，并计算出归因分数，进而推导出 2000 年至 2018 年间归因于核电站的死亡人数。作者声称，他们的方法论和结果为开展更大规模的研究项目提供了科学依据和公共卫生正当性。

But proximity is not exposure. We have methods of measuring exposure for nuclear power plant workers. While the radiation exposure of nuclear workers will always be greater than or equal to that received by the surrounding public, most of the closely monitored US nuclear workforce receive no measurable annual dose. When workers are exposed to radiation, the average dose received is only 2 percent of the occupational limit. If operators and workers who are on-site at nuclear power plants receive an annual dose between zero and one-fiftieth of the occupational limit, how is it possible that residents 5, 10, 25, 50, 120, or 200 kilometers away would receive any measurable dose from the same plant?

但邻近并不等于暴露。我们有测量核电站工作人员辐射暴露的方法。虽然核电站工作人员受到的辐射暴露总是大于或等于周边公众，但大多数受到严密监测的美国核电从业人员每年的辐射剂量都在可测量范围之外。当工人接触辐射时，其平均剂量仅为职业限值的 2%。如果身处核电站现场的操作员和工人的年辐射剂量都在零到职业限值的五十分之一之间，那么居住在 5、10、25、50、120 或 200 公里外的居民怎么可能从同一座电站受到任何可测量的辐射剂量呢？

In talks, the authors hedge that their papers are merely ecological studies that show association, but never prove causality. Ecological studies are used to understand the relationship between outcome and exposure at a population level. This leads us to ask: what would the mechanism of exposure be? Well, according to the authors, we can just ignore the broader literature and physics, and instead make up exposure pathways and mechanisms. The use of an “ecological study” allows a lot of leeway in terms of explaining the broader world.

在演讲中，作者们含糊其辞地表示，他们的论文仅仅是生态学研究，旨在展示相关性，而非证明因果关系。生态学研究用于理解群体层面的结果与暴露之间的关系。这引出了一个问题：暴露的机制究竟是什么？好吧，根据作者的说法，我们可以直接忽略更广泛的文献和物理学知识，转而编造暴露途径和机制。使用“生态学研究”这一标签，为解释更广阔的世界提供了很大的回旋余地。

Over the last several months, we have replicated the results of these papers. The authors supplied us with eight lines of code and answered a couple of questions about the covariates, which did not replicate the results. Most of our replication was done through first principles combined with trial and error. Once we were reasonably close to the results of the first national study on cancer mortality, we took the methodology and applied it to numerous other landmarks.

在过去的几个月里，我们复现了这些论文的结果。作者向我们提供了八行代码并回答了关于协变量的几个问题，但这些并不能复现出他们的结果。我们大部分的复现工作是通过第一性原理结合反复试验完成的。一旦我们得出的结果与第一项全国性癌症死亡率研究的结果相当接近，我们就将这套方法论应用到了其他众多的地标上。

Ridiculous things you can “prove” caused cancer mortality

你可以“证明”导致癌症死亡的荒谬事物

Everything causes cancer. Sounds cliché; maybe those California warning tags were right all along. But thanks to the methodology created by Alwadi et al., we can now prove that anything and everything causes cancer. Oh, sorry, that is too strong of an assertion. To use the authors’ words, since they have claimed their papers don’t prove causality, we can create an association between any physical landmark and cancer and, from that association, figure out how much cancer is attributable to that thing. Which is totally not the same as saying “that thing causes cancer.”

万物皆致癌。听起来像是陈词滥调；也许加州的那些警告标签一直都是对的。但多亏了阿尔瓦迪等人创造的方法论，我们现在可以证明任何事物、所有事物都会导致癌症。哦，抱歉，这个说法太绝对了。用作者们的话说，既然他们声称自己的论文并未证明因果关系，那么我们就可以在任何物理地标与癌症之间建立关联，并从这种关联中计算出有多少癌症归因于该事物。这与说“该事物导致癌症”完全不是一回事。

For instance, living near a private four-year university is associated with a 15-fold increase in cancer mortality when compared to living near a nuclear power plant. Costco has the largest effect of all the locations we have tested. Over 2.2 million cancer deaths can be attributed to Costco; that’s more than 20% of all cancer deaths between 2000 and 2018. Hot dogs, bulk spices, and reasonably priced clothes come with a cost. But it goes to show that the authors’ choice of nuclear power…

例如，与居住在核电站附近相比，居住在四年制私立大学附近与癌症死亡率增加 15 倍有关。在我们测试的所有地点中，Costco 的影响最大。超过 220 万例癌症死亡可归因于 Costco；这占了 2000 年至 2018 年间所有癌症死亡人数的 20% 以上。热狗、大包装香料和价格合理的衣服都是有代价的。但这恰恰说明了作者选择核电作为研究对象……