"Weight of evidence" (WOE) is a common term in the published scientific and policy-making literature, most often seen in the context of risk assessment (RA). Its definition, however, is unclear. A systematic review of the scientific literature was undertaken to characterize the concept. For the years 1994 through 2004, PubMed was searched for publications in which "weight of evidence" appeared in the abstract and/or title. Of the 276 papers that met these criteria, 92 were selected for review: 71 papers published in 2003 and 2004 (WOE appeared in abstract/title) and 21 from 1994 through 2002 (WOE appeared in title). WOE has three characteristic uses in this literature: (1) metaphorical, where WOE refers to a collection of studies or to an unspecified methodological approach; (2) methodological, where WOE points to established interpretative methodologies (e.g., systematic narrative review, meta-analysis, causal criteria, and/or quality criteria for toxicological studies) or where WOE means that "all" rather than some subset of the evidence is examined, or rarely, where WOE points to methods using quantitative weights for evidence; and (3) theoretical, where WOE serves as a label for a conceptual framework. Several problems are identified: the frequent lack of definition of the term "weight of evidence," multiple uses of the term and a lack of consensus about its meaning, and the many different kinds of weights, both qualitative and quantitative, which can be used in RA. A practical recommendation emerges: the WOE concept and its associated methods should be fully described when used. A research agenda should examine the advantages of quantitative versus qualitative weighting schemes, how best to improve existing methods, and how best to combine those methods (e.g., epidemiology's causal criteria with toxicology's quality criteria).

Causation is an essential concept in epidemiology, yet there is no single, clearly articulated definition for the discipline. From a systematic review of the literature, five categories can be delineated: production, necessary and suYcient, suYcient-component, counterfactual, and probabilistic. Strengths and weaknesses of these categories are examined in terms of proposed characteristics of a useful scientific definition of causation: it must be specific enough to distinguish causation from mere correlation, but not so narrow as to eliminate apparent causal phenomena from consideration. Two categoriesproduction and counterfactual-are present in any definition of causation but are not themselves suYcient as definitions. The necessary and suYcient cause definition assumes that all causes are deterministic. The suYcient-component cause definition attempts to explain probabilistic phenomena via unknown component causes. Thus, on both of these views, heavy smoking can be cited as a cause of lung cancer only when the existence of unknown deterministic variables is assumed. The probabilistic definition, however, avoids these assumptions and appears to best fit the characteristics of a useful definition of causation. It is also concluded that the probabilistic definition is consistent with scientific and public health goals of epidemiology. In debates in the literature over these goals, proponents of epidemiology as pure science tend to favour a narrower deterministic notion of causation models while proponents of epidemiology as public health tend to favour a probabilistic view. The authors argue that a single definition of causation for the discipline should be and is consistent with both of these aims. It is concluded that a counterfactually-based probabilistic definition is more amenable to the quantitative tools of epidemiology, is consistent with both deterministic and probabilistic phenomena, and serves equally well for the acquisition and the application of scientific knowledge. (J Epidemiol Community Health 2001;55:905-912)

This paper is based on a workshop held in Oslo, Norway in November 2013, in which experts discussed how to reach consensus on the healthiness of red and processed meat. Recent nutritional recommendations include reducing intake of red and processed meat to reduce cancer risk, in particular colorectal cancer (CRC). Epidemiological and mechanistic data on associations between red and processed meat intake and CRC are inconsistent and underlying mechanisms are unclear. There is a need for further studies on differences between white and red meat, between processed and whole red meat and between different types of processed meats, as potential health risks may not be the same for all products. Better biomarkers of meat intake and of cancer occurrence and updated food composition databases are required for future studies. Modifying meat composition via animal feeding and breeding, improving meat processing by alternative methods such as adding phytochemicals and improving our diets in general are strategies that need to be followed up.

The possible relationship between dietary cholesterol and cardiac outcomes has been scrutinized for decades. However, recent reviews of the literature have suggested that dietary cholesterol is not a nutrient of concern. Thus, we conducted a meta-analysis of egg intake (a significant contributor to dietary cholesterol) and risk of coronary heart disease (CHD) and stroke. A comprehensive literature search was conducted through August 2015 to identify prospective cohort studies that reported risk estimates for egg consumption in association with CHD or stroke. Random-effects meta-analysis was used to generate summary relative risk estimates (SRREs) for high vs low intake and stratified intake dose-response analyses. Heterogeneity was examined in subgroups where sensitivity and meta regression analyses were conducted based on increasing egg intake. A 12% decreased risk (SRRE = 0.88, 95% confidence interval [CI], 0.81-0.97) of stroke was observed in the meta-analysis of 7 studies of egg intake (high vs low; generally 1/d vs <2/wk), with little heterogeneity (p-H = 0.37, I = 7.50). A nonstatistically significant SRRE of 0.97 (95% CI, 0.88-1.07, p-H = 0.67, I = 0.00) was observed in the meta-analysis of 7 studies of egg consumption and CHD. No clear dose-response trends were apparent in the stratified intake meta-analyses or the meta regression analyses. Based on the results of this meta-analysis, consumption of up to one egg daily may contribute to a decreased risk of total stroke, and daily egg intake does not appear to be associated with risk of CHD. Key Teaching Points: • The role of egg consumption in the risk of stroke and coronary heart disease has come under scrutiny over many years. • A comprehensive meta-analysis of prospective cohort studies that reported risk estimates for egg consumption in association with CHD or stroke was performed on the peer-reviewed epidemiologic literature through August 2015. • Overall, summary associations indicate that intake of up to 1 egg daily may be associated with reduced risk of total stroke. • Overall, summary associations show no clear association between egg intake and increased or decreased risk of CHD. • Eggs are a relatively low-cost and nutrient-dense whole food that provides a valuable source of protein, essential fatty acids, antioxidants, choline, vitamins, and minerals.

No abstract