ArticleAnnals of epidemiology2010
Incorporating individual-level distributions of exposure error in epidemiologic analyses: an example using arsenic in drinking water and bladder cancer.
Article in Annals of epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Environmental Nonessential Element Exposure and Urologic Cancer: A Systematic Review and Meta-Analysis.JAMA network open · 2026Pooled it
- Association between lifetime exposure to inorganic arsenic in drinking water and coronary heart disease in Colorado residents.Environmental health perspectives · 2015Article
- The two-dimensional Monte Carlo: a new methodologic paradigm for dose reconstruction for epidemiological studies.Radiation research · 2015Article
- Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.PloS one · 2015Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
purposeEpidemiologic analyses traditionally rely on point estimates of exposure for assessing risk despite exposure error. We present a strategy that produces a range of risk estimates reflecting distributions of individual-level exposure.
methodsQuantitative estimates of exposure and its associated error are used to create for each individual a normal distribution of exposure estimates which is then sampled using Monte Carlo simulation. After the exposure estimate is sampled, the relationship between exposure and disease is evaluated; this process is repeated 99 times generating a distribution of risk estimates and confidence intervals. This is demonstrated in a bladder cancer case-control study using individual-level distributions of exposure to arsenic in drinking water.
resultsSensitivity analyses indicate similar performance for categorical or continuous exposure estimates, and that increases in exposure error translate into a wider range of risk estimates. Bladder cancer analyses yield a wide range of possible risk estimates, allowing quantification of exposure error in the association between arsenic and bladder cancer, typically ignored in conventional analyses.
conclusionsIncorporating distributions of individual-level exposure error results in a more nuanced depiction of epidemiologic findings. This approach can be readily adopted by epidemiologists assuming distributions of individual-level exposure.
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Registered trials
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