China Study

aka China Project... The book is "loosely based"[9] on the China–Cornell–Oxford Project, a 20-year study—described by The New York Times as "the Grand Prix of epidemiology"—conducted by the Chinese Academy of Preventive Medicine, Cornell University, and the University of Oxford. T. Colin Campbell was one of the study's directors.

a "survey of death rates for twelve different kinds of Cancer for more than 2,400 counties and 880 million (96%) of their citizens" combined to study the relationship between various mortality rates and several dietary, lifestyle, and environmental characteristics in 65 mostly rural counties in China conducted jointly by Cornell University, Oxford University, and the Chinese Academy of Preventive Medicine over the course of twenty years. (The "Project" was the original research, the "Study" is the book about it).

The authors conclude that diets high in animal protein (including casein in cow's milk) are strongly linked to diseases such as heart disease, cancer, and Type 2 diabetes. The authors recommend that people eat a whole food, plant-based diet and avoid consuming beef, poultry, eggs, fish, and milk as a means to minimize and/or reverse the development of chronic diseases. (Good Diet)

http://en.wikipedia.org/wiki/The_China_Study

Mar'2009 piece by Harriet Hall

Jul'2010 piece by Harriet Hall based on new analysis of raw data by Denise Minger. Denise Minger devoted a month and a half to examining the raw data to see how closely Campbell’s claims aligned with the data he drew from; she found many weaknesses and errors... The data do show that cholesterol is positively associated with various cancers, that cholesterol is positively associated with animal protein, and that cholesterol is negatively associated with plant protein. So by indirect deduction they assume that animal protein is associated with cancers and that reducing intake is protective. But if you compare animal protein intake directly with cancer, there are as many negative correlations as positive, and not one of those correlations reaches a level of statistical significance.