Read This Before You Start Proteinmaxxing | Essay

From proteinmaxxing and fibermaxxing, today’s extreme fad diets are couched in the language of optimization. Health influencers and celebrities say we need to squeeze as much of these specific nutrients into our meals as possible to maximize how we look or how long we live. Diet, like so many aspects of our lives, has become something that everyone should optimize. While it sounds nice in theory to strive for the best diet, what would that mean? The history of diet optimization suggests that the question itself is ludicrous.

To set the stage for optimal dieting, we need to go back to the early 20th century. Scientists discovered that a constellation of mysterious illnesses, including beriberi, pellagra, and rickets, was caused not by germs but by a lack of certain chemical compounds we now know as vitamins. Your body needs vitamins to function, but can’t synthesize these organic molecules on its own. They have to be consumed in food. In the 1910s, a unified theory of vitamins emerged, and small additions to monotonous diets effectively delivered miracle cures to those suffering from deficiency diseases across the globe.

Public health officials sought to get the new science of vitamins out to families to prevent disease and improve well-being. In the United States, Hazel Stiebeling—a Columbia University-trained chemist who had written her PhD thesis on vitamins A and D—was one of the figures who took charge, leading the food economics division of the U.S. Department of Agriculture (USDA).

One of Stiebeling’s central tasks was modernizing the USDA’s dietary recommendations to incorporate our new scientific knowledge of vitamins. She published her first plans, “Diets to Fit the Family Income,” in 1936 with co-author Rowena Carpenter. In the midst of the Great Depression, they put forward proposals that could meet basic dietary requirements for little money.

Their “minimum cost” diet ran around $120 per person per year at 1935 prices. It included a pint of milk, three to four servings of vegetables, and at least one serving of potatoes each day, adding cereal for breakfast and bread with every meal. They suggested consuming citrus or tomatoes two to three times per week, and meat, fish, or eggs three to four times a week. The diet even budgeted for some occasional desserts.

While most people would look at Carpenter and Stiebeling’s diet plan and see a reasonable and modest proposal, University of Chicago economist George Stigler was deeply annoyed. He saw government bureaucrats falsely using the language of science to make recommendations about how people should live.

Stigler set out to prove Stiebeling and Carpenter’s diets were far from “minimum cost.”

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Combining recommendations from the National Research Council and data from the Bureau of Labor Statistics with some mathematical heuristics, Stigler found a combination of foods that would cost a person only $40 per year, more than two and a half times less expensive than Carpenter and Stiebeling’s plan. He had cracked the code of savingsmaxxing. But what was in this diet? Every day, a person would consume one pound of flour, two ounces of evaporated milk, five ounces of cabbage, one ounce of spinach, and five cans of navy beans.

That’s not a diet! Or at least not one any reasonable person would be satisfied eating.

Stigler, a prickly critic, of course knew this diet was gross and that many subjective factors influenced how every person eats, from taste to company and culture. He grumbled that the nutritional recommendations were based on guesswork, often inflated by 50% just to be safe. Scientists knew nothing about the extent of individual variation in nutritional needs. The amount of nutrients in cooked food varied depending on its preparation. A Granny Smith apple would have a different amount of vitamin C than a Red Delicious. There was so much complexity that writing down a single optimal answer for everyone was impossible.

With so much uncertainty, Stigler thought it was inappropriate for the government to recommend what people should eat at all. He warned that these recommendations, with their appeals to scientific expertise, might be mistaken for rules. The United States was home to people with different preferences, practices, and beliefs, and a uniform recommendation couldn’t satisfy all of them. Indeed, recent fights over the food pyramid show that government recommendations of what to eat remain fraught.

Stiebeling and Stigler, and their views on diet recommendations, are emblematic of the diametrically opposed political philosophies of the two parties that have governed the United States since the 1940s. Stiebeling was a liberal technocrat who believed improvements in policy would lead to improvements in citizens’ lives. She invented the term “dietary allowances” and launched the first school lunch programs. Stigler was a laissez-faire economist who believed people are best off left to figure out what works for themselves. With Milton Friedman, Stigler became a key leader of the Chicago School of Economics. Stigler also coined the term “regulatory capture” and won the Nobel Prize in economics in 1982. Stiebeling and Stigler’s fights about diet would signal the theme and tenor of American political arguments for decades to come.

But there are also lessons for us outside the political sphere. In undergraduate computer science classes about algorithms and operations research, we still teach Stigler’s diet problem as a prototypical example of linear programming. The backbone of modern computational optimization, linear programming is used in tasks as diverse as scheduling flight times to transporting goods from warehouses to shops. Optimization can be useful, but only in places where the models accurately and precisely reflect reality and a singular objective function, like the shortest path, reasonably captures the problem you are trying to solve.

Real life seldom meets those criteria, and optimization rarely applies to anything we do. This is why optimizing a single objective gives you grotesque answers like a pound of flour and a can of navy beans. Optimization can only fill in what you model, and if you leave out details, maxxing will give you something you didn’t expect and probably didn’t really want.

Even the simplest optimization problems are loaded with approximations, idealizations, and value judgments. These issues do not go away when we try to optimize more complex and challenging problems. The way out of the culture of maxxing is to recognize that our goals in life are never reducible to a single mathematical formula.

Benjamin Recht is a professor of electrical engineering and computer sciences at the University of California, Berkeley, and regularly blogs at argmin.net. This essay draws from research from his most recent book, The Irrational Decision.

Primary editor: Jackie Mansky | Secondary editor: Sarah Rothbard