Results from nutritional studies that evaluate the potential association between a food and cancer are often widely reported with attention-grabbing headlines. These reports, including the press releases announcing the study results, often report a percent risk, such as food X is linked to a 25% increase in the risk of cancer.

It is important to correctly interpret the results of these nutritional studies and translate their results in context, particularly when reading the (sometimes sensational) headlines that have the potential to provoke anxiety about cancer risk.

Study Design

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The gold standard for studies that generate data about a topic is the randomized controlled trial, in which a research cohort is compared with a control group.1 Most nutritional studies, however, are epidemiologic in nature, meaning they evaluate potential relationships between a food or dietary pattern and risk based on observations of individuals in a group. This can be done prospectively or retrospectively. Another approach is a case-control study, in which cases of a disease are “matched” to similar individuals without the disease and their characteristics are observed.

It is important to recognize that epidemiologic studies are not designed to identify a causal relationship — they cannot definitively determine whether a food or dietary pattern causes cancer or protects against the development of malignancies.

Epidemiologic studies, however, are important for generating hypotheses about potential relationships. They can identify a potential association between a food or dietary pattern and cancer, but additional studies are needed to establish the plausibility of a causal link. Although a randomized controlled trial would be the ideal approach to test a causal link, this is often not feasible for nutritional studies. Thus, any associations are typically extracted from the results of multiple epidemiologic studies conducted in different populations by different researchers.

All studies are potentially confounded by bias, including randomized controlled trials.1 Specifically, in nutrition studies, dietary intake is often determined by patient-reported questionnaires, which is known to be inaccurate. Individuals have difficulty remembering their dietary intakes and/or lie about their intake to match what they believe is socially acceptable. In addition, dietary-intake patterns may vary within individuals, which also makes accurate recording difficult. Similarly, dietary intake patterns vary between different individuals, even among those individuals who appear to have similar habits (eg, those who consume a Mediterranean diet or those who have a standard American diet).

Dietary intake can also be linked to other variables that affect disease, such as smoking, socioeconomic status, family history, geographic area, or ethnicity. Some studies adjust their data and conclusions according to these variables, while other study authors do not control for these differences.1

Sample size is also important to consider.2 A small study size can make it difficult to determine if there is an association present because of too few events or exposures, and it can make it difficult to extrapolate the overall findings to a larger population. Although a large sample size is generally preferable, a very large sample size can also amplify results, causing false positives that are likely not clinically relevant. It is important to be aware of the sample size for each study, and how the size of the study group could influence the interpretation of the results.