[jimbo2012]

A second option proceeds 'outwardly' to better understand the broader implications of a series of findings, or experiments. I did some of the first but eventually preferred the second, taking each finding not as something to refine into 'perfection' but to ask whether it was sufficiently compelling to suggest the next obvious experiment that eventually might lead to an important network of findings. Having done both, I strongly prefer the latter option because the whole, indicated by a network of findings, is often far more useful than its parts. I also believed that this second option had more potential to meet the interests of the public who funded our research. I also am very much motivated by the fact that there are far too many individuals needlessly paying a heavy personal price in their health for not having access to information of this kind that could have saved their lives, a moral issue for me. Under no circumstances was I controlled by what my personal preferences might have been!

In the case of our project in China, I believe that its design, its uniqueness and its execution are virtually without parallel in its quality-thanks very much to my colleagues. However, as trained people know, making specific inferences about causality is not appropriate in a study of this kind. The concept of 'ecologic fallacy', wherein a univariate correlation is improperly used to diagnose or to treat an individual person, is well known. In contrast, if one initially has a reasonably convincing and biologically plausible body of data and if the data are appropriately qualified, then using a study like to this to see if there is consistency, is appropriate This is appropriate in my opinion if the hypothesis being addressed represents a comprehensive causal effect where many factors are acting in concert and where there may be multiple ways of examining the data (e.g., multiple factors being consumed, multiple clinical biomarkers of factor tissue status, multiple methods of measurement and, perhaps, even multiple outcomes). This is what we did. We began with a collection of previously developed cause-effect models (previously published) that we could test for consistency with the China data. We found on balance considerable support in the China database for these models. As I've said many times, not all the evidence in the China database supported this conclusion, although the large majority did. To find this degree of consistency in a population mostly using a low fat, high fiber, whole plant-based foods with little or no processed foods--where I had thought that we would see little or nothing--was impressive. One cannot, as Denise has done, rely on univariate correlations to make conclusions, especially when they are focused on specific foods for specific diseases--it is too easy to find what one wants to find.

I know that this discussion between Denise and me is difficult to judge by readers of this exchange without having access to the raw data base and without knowing how to use or interpret it. Accepting this, therefore, I suggest that, in the final analysis, the reliability of any conclusion about complex cause-effect issues should be judged by its ability to predict health outcomes. In this case, the results of people using a diet of whole, plant-based foods, as shown by physician colleagues (previously mentioned, McDougall, Esselstyn, Ornish, Barnard, Fuhrman, et al) as well as by many of the readers of our book are nothing less than incredible. There is nothing else in medicine like it!