Multi-causality,timing and the disease process David Gee, european environment agency 28 July 2006 Vineis and Kriebel refer to a component cause completing the causal pie, and thus “initiating the disease process”. However, matters appear to be more complicated than this. Any complex disease process that leads to say cancer, asthma, or neuro-developmental diseases can involve some, or all of, at least seven stages: preparation; initiation; promotion; retardation; progression, disease onset; and the strengthening/weakening of the severity and /or prevalence of the disease. (“Preparation” includes the genetic, hormonal, immune, age, sex, etc. status of the host) Each of these stages could be triggered by co-causal factors. Some factors may operate at several stages of the disease process, and via each of several causal chains. Common diseases, such as cancer, could have each of their stages triggered by different, or sometimes overlapping, co-causal factors operating via several causal chains. Identifying co-causal factors in such disease processes (and eventually understanding their different mechanisms of action) will be challenging.The critical issue of “the timing of the exposure, or dose”, which the authors emphasise, further complicates analysis of disease causation. Timing is not only relevant to the developmental stage reached at the time of exposure/dose (e.g. day x being sensitive to that same exposure whilst, day x plus or minus 1 day may not be so), but also to each of the above stages reached in the disease process. The same exposure may have, or may not have, biologically relevant impact on the disease process, depending on the stage reached in the disease process at the time of exposure. The amount of exposure ( biologically available dose) at the critical times may also determine impact. Too little or too much exposure may have no biological impact compared to the critical level of exposure delivered at the “right” time and at the “right” stage of the disease process.This view of multi-causality and of multi-stage disease processes also has implications for the conventional methods of identifying attributable fractions of disease, and their later use in estimating “environmental burden of disease”. The authors recommend “considerable humility” and “caution” when interpreting estimated attributable fractions because of the likelihood that the standard methods of estimating “statistical fractions” underestimate the “etiological fraction”, citing Greenland and Robins. However, the example which Vineis and Kriebel describe as “the most important” limitation of standard methods, ie. omitting to include the moving forward in time of the onset of a disease, is likely to be less important than the logical implication of inter-linked causal chains for attributable fractions of disease.For example in Europe, the “environmental burden of disease” (EBOD) using conventional methods, is estimated to be around 5 %, whilst the oft cited Doll/Peto estimation of the occupational causes of cancer comes out at about the same fraction. Both are likely to be large underestimates. If each of several co-causal and inter-dependent factors in a multi-causal chain are necessary (but not sufficient) links in the chain, each co-causal factor is logically 100 % “responsible” for the disease, as Rothman has pointed out. The policy implications for disease prevention of this very different approach to EBOD are interesting. Competing interests none-except I am acknowledged at the end of their article as having provided encouragement and suggestions.