38 THE CHINA STUDY
one solution: start doing fundamental laboratory research to see not only
if, but also how, consuming more protein leads to more cancer. That's
exactly what I did. It took me farther than I had ever imagined. The ex-
traordinary findings my colleagues, students and I generated just might
make you think twice about your current diet. But even more than that,
the findings led to broader questions, questions that would eventually
lead to cracks in the very foundations of nutrition and health.THE NATURE OF SCIENCE-WHAT YOU NEED TO KNOW
TO FOLLOW THE RESEARCH
Proof in science is elusive. Even more than in the "core" sciences of biol-
ogy, chemistry and physics, establishing absolute proof in medicine and
health is nearly impossible. The primary objective of research investiga-
tion is to determine only what is likely to be true. This is because research
into health is inherently statistical. When you throw a ball in the air, will
it come down? Yes, every time. That's physics. If you smoke four packs a
day, will you get lung cancer? The answer is maybe. We know that your
odds of getting lung cancer are much higher than if you didn't smoke, and
we can tell you what those odds (statistics) are, but we can't know with
certainty whether you as an individual will get lung cancer.
In nutrition research, untangling the relationship between diet and
health is not so straightforward. Humans live all sorts of different ways,
have different genetic backgrounds and eat all sorts of different foods.
Experimental limitations such as cost restraints, time constraints and
measurement error are significant obstacles. Perhaps most importantly,
food, lifestyle and health interact through such complex, multifaceted
systems that establishing proof for anyone factor and anyone disease is
nearly impossible, even if you had the perfect set of subjects, unlimited
time and unlimited financial resources.
Because of these difficulties, we do research using many different
strategies. In some cases, we assess whether a hypothetical cause pro-
duces a hypothetical effect by observing and measuring the differences
that already exist between different groups of people. We might observe
and compare societies who consume different amounts of fat, then ob-
serve whether these differences correspond to similar differences in the
rates of breast cancer or osteoporosis or some other disease condition.
We might observe and compare the dietary characteristics of people who
already have the disease with a comparable group of people who don't
have the disease. We might observe and compare disease rates in 1950