• Low expected statistical power. Doses resulting from monitored and reported radioactive effluent releases from nuclear facilities are expected to be low. As a consequence, epidemiologic studies of cancer risk in populations near nuclear facilities may not have adequate statistical power to detect the presumed small increases in cancer risks arising from these monitored and reported releases.

The committee paid close attention to these challenges as it assessed the scientific merit of various epidemiologic study designs.

FINDING 2: An assessment of cancer risks in populations near nuclear facilities could be carried out using several study designs. Each design has strengths and limitations for estimating cancer risks.

  • Risk-projection models estimate cancer risks by combining population radiation dose and/or dose surrogate (e.g., distance and direction from a nuclear facility) estimates with risk coefficients derived from epidemiologic studies of other exposed populations, for example, Japanese atomic bombing survivors. Risk-projection models can be used to estimate population-based cancer risks for any facility type, population size, and time period. However, because risk estimates are based on extrapolations from other epidemiologic studies and not on actual cancer incidence and/or mortality rates in populations near nuclear facilities, risk-projection models cannot be used to assess whether any predicted excess cancer risks correspond to observed patterns of cancer incidence or mortality.
  • Ecologic studies estimate cancer risks by comparing observed cancer incidence and/or mortality rates in populations, considered as a group rather than as individuals, as a function of average radiation doses and/or dose surrogates for those populations. This design allows for the study of multiple cancer types during past and recent times, which helps to improve statistical power and provides a comprehensive picture of cancer risks. However, ecologic studies involve a large number of comparisons among population age groups, nuclear facilities, years of operation, and cancer types. This can lead to false associations resulting from chance alone. Moreover, ecologic studies can account only for population characteristics and potential confounding factors using group averages that are available from the decennial census and from survey information that can be linked to the census data (such as the American Community Survey). Individual characteristics can diverge sharply from group averages.
  • Cohort studies estimate cancer risks by following individuals for a

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