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This, then, is the case against fat: America, we are told, is on the verge of eating itself to death. The core belief of those prosecuting this case is that the BMI tables testify to a strong, predictable relationship between increasing weight and increasing mortality. That, after all, is what most people assume when they read that medical and public health authorities have determined a BMI of 25 or above is hazardous to a person's health. This belief, however, is not supported by the available evidence.
A 1996 project undertaken by scientists at the National Centre for Health Statistics and Cornell University analysed the data from dozens of previous studies, involving a total of more than 600,000 subjects with up to a 30-year follow-up. Among non-smoking white men, the lowest mortality rate was found among those with a BMI between 23 and 29, which means that a large majority of the men who lived longest were "overweight" according to government guidelines. The mortality rate for white men in the supposedly ideal range of 19 to 21 was the same as that for those in the 29 to 31 range (most of whom would be defined now as "obese"). In regard to non-smoking white women, the study's conclusions were even more striking: the BMI range correlating with the lowest mortality rate was extremely broad, from around 18 to 32, meaning a woman of average height could weigh anywhere within an 80-pound range without seeing any statistically significant change in her risk of premature death.
In almost all large-scale epidemiological studies, little or no correlation between weight and health can be found for a large majority of the population - and indeed what correlation does exist suggests that it is more dangerous to be just a few pounds "underweight" than dozens of pounds "overweight". So, let us look at the most cited studies for the proposition that "overweight" is a deadly epidemic in America today. Anyone who bothers to examine the evidence in the case against fat with a critical eye will be struck by the radical disconnect between the data in these studies and the conclusions their authors reach.
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