Obesity and SNAP: the overlooked IQ connection

I saw the below tweet going massively viral, amassing 42k ‘likes’ in a day, surpassing competing high-stakes stories at the time, such as Venezuela. This indicates considerable interest in this topic.

This observation is often used to justify restricting SNAP benefits to “essentials,” excluding soda and other junk food, under the assumption that recipients are wasting benefits on unhealthy food and becoming obese as a result. Indeed, many studies, along with extensive anecdotal evidence, indicate that SNAP recipients are disproportionately likely to be obese (see, for example, CDC obesity data, JAMA research on poverty and obesity, and NPR’s overview of the poverty–obesity link).

There is some truth to this perception: I’m sure we’ve all seen obese, low-income people in the checkout line and wondered to ourselves why they are making such poor life choices, and worse, are being subsidized for it at taxpayer expense–both for junk food and increased medical costs incurred by being obese. However, this framing overlooks an important inconsistency: many non-SNAP individuals also consume calorie-dense, unhealthy food without becoming obese.

Thus, I hypothesize that lower cognitive ability may be associated with greater metabolic efficiency–meaning weight gain occurs more readily–whereas higher cognitive ability may confer relative resistance to weight gain, holding diet constant. The question, then, is whether these differences reflect substantially higher caloric intake, or whether biological differences in metabolism better explain the disparity.

Consider high rates rates of obesity among blue-collar workers, compared to lean yet sedentary office workers. Truck drivers famously have high rates of obesity, and this is often blamed on inactivity by sitting in a truck all day. Yet coders sit at a computer all day, but have much lower rates of obesity. In regard to diets, true, truck drivers eat a lot of junk food, but so do coders. Tech companies, for instance, are well known for offering abundant spreads of high-calorie meals and snacks. Fully-stocked cafeterias or free meal delivery are one of the biggest perks of working at a top tech company.

From a related post, “Blaming Obesity on Low IQs”:

Again, confirming my IQ point above, it’s white-collar office-job-types who also tend to be thin despite their jobs not entailing much physical activity. Conversely, less intelligent blue-collar workers, such as construction or road work, are almost all overweight despite having jobs that entail physical activity. Bill Gates was wire-thin in his younger years despite his job literally involving sitting at a computer all day. On his résumé he lists being 5’10” and weighing 130 lbs, which is a BMI of 18.7-borderline underweight.

Prominent billionaires such as Bill Gates, Mark Zuckerberg, Charlie Munger, and Warren Buffett are frequently cited for having poor diets, yet they generally avoid obesity. Warren Buffett is legendary for his love of Coca-Cola and aversion to healthy food. Or Bill Gates’ love of cheeseburgers, from the above link, “Gates also apparently loves cheeseburgers. Joe Cerrell, managing director of global policy and advocacy at the Bill & Melinda Gates Foundation, has said that anyone who has lunch with Gates should expect to have cheeseburgers.” Zuckerberg loves huge, fatty steaks and eating 4,000 kcal/day of McDonald’s, yet is far from obese. Likewise, software developers often pull all-nighters fueled by pizza and junk food without obvious long-term weight gain.

Yet SNAP recipients appear especially vulnerable to weight gain when consuming similar foods, while weight gain seems far more elusive for others. This raises an important question: why do low-income individuals appear to gain weight so easily under dietary conditions that do not produce the same outcomes for higher-income groups?

I propose that the underlying factor is IQ. Human Biodiversity (HBD) research is unmatched in its predictive power across a wide range of outcomes. Too often, what are framed as purely environmental explanations–such as laziness or gluttony–are actually masking underlying biological differences. Too much discussion places blame on the individual and not on genes. The latter possibility is rarely explored in public discussions.

In the case of SNAP recipients, who tend to score lower on various IQ proxies such as educational attainment and related indicators, it is plausible that lower cognitive ability is associated with stronger preferences for hyper-palatable, calorie-dense foods, as well as a greater aversion to exercise, and all compounded by a slower metabolism: a triple whammy. These tendencies would naturally increase the risk of obesity.

Indeed, a lower IQ is positively correlated with worse life choices:

We know that intelligent people have more self-control and make better decisions in general — they’re less likely to play the lottery, more likely to follow medical advice, less likely to die in accidents. As a consequence, they tend to flourish in an environment free of normative constraints. They may experiment with drugs without ever getting addicted. They may dabble in polyamory without wrecking their marriage. They may coast on their achieved identity, dismissing traditions as stifling or unnecessary.

Yet when people of low intelligence find themselves in the very same environment, they tend to flounder. They may abuse drugs or cheat on their spouse. They might crave traditions that afford a sense of belonging.

So regarding food, perhaps less intelligent people simply lack the inhibition to know when to stop overeating, compared to smart people.

This framing also helps explain an apparent paradox noted earlier: why high-IQ individuals with objectively poor diets and minimal exercise often avoid obesity. As the joke goes, the only unused room in Bill Gates’s mansion is his home gym. Despite consuming unhealthy food and rarely exercising, many high-IQ individuals remain lean. The implication is that intelligence itself may confer metabolic, behavioral, or regulatory advantages that reduce susceptibility to weight gain, even under similar dietary conditions.

Another factor often discussed in the Human Biodiversity (HBD) literature is race. SNAP recipients are disproportionately Black/African American (non-Hispanic): roughly 26% of recipients, compared to about 13% of the general U.S. population. Average group differences in measured IQ scores between Black and White populations–often cited as approximately one standard deviation–are frequently invoked in this literature as potential correlates of downstream health and behavioral outcomes.

One study examining so-called hypometabolizers–defined as obese individuals with abnormally low resting energy expenditure–found substantial racial and sex stratification. Approximately 75% of individuals classified as hypometabolizers were Black, with most of the remainder Asian, and roughly 80% were women. By contrast, hypermetabolizers–individuals with unusually high resting energy expenditure–were overwhelmingly White (about 95%), with only a small fraction classified as Black, shown below:

[Although the high incidence (25%) of the ‘hypometabolizers’ phenotype in Asians may contradict the IQ link, this is presumably among South Asians, who have lower IQs compared to leaner East Asians.]

As supporting evidence, many studies also show Blacks, especially Black women, have much lower metabolisms, controlling for weight, height , physical activity level, and lean body mass, compared to Whites. This again ties with lower IQs for this group, SNAP usage, and high rates of obesity. This also fits in with the stereotype of obese Black women commonly seen buying junk food with SNAP. It’s bad enough that these people make poor food choices, but this is compounded by having slow metabolisms.

Indeed, from the above study, physical activity fails to explain differences of metabolic rates between groups:

A similar pattern is seen worldwide, with high rates of obesity in lower-IQ regions; e.g. the Middle East, South America, Pacific Islands, or the Southern United States. The default or go-to solution of “increasing physical activity or adding muscle mass,” doesn’t explain how Polynesians, despite having a lot of muscle mass, have among the highest rates of obesity in the world, but IQ does. These people are not that smart and burn too few calories despite being muscular. This also shows that physical activity alone will not be a panacea. The solutions are to consume fewer calories or to increase metabolism in some way. GLP-1 drugs are a promising start, as they suppress appetite.

Online, similar patterns appear across fitness and health communities–such as bodybuilding and dieting–where the putative goal is leanness. On social media, I have observed that users with proxies or indicators of higher cognitive ability (for example, high-paying jobs or top test scores) often appear to have faster metabolisms, controlling for weight and height. They tend to get lean more easily and while eating more food, compared with others in the same communities. Blacks and Hispanics struggle the most at weight loss or getting lean and have especially slow metabolisms, in accordance with lower mean IQs. A similar pattern holds for less intelligent Whites.

Not just limited to dieting, individuals with lower cognitive performance seem to show poorer physical performance, whether in strength (e.g. weightlifting) or endurance (e.g. running). Taken together, these patterns are consistent with the possibility of an underlying biological or genetic correlation linking traits that are usually treated as separate–such as metabolism, cardiovascular capacity, strength, and cognitive ability. Perhaps being smarter means better neurological recruitment of muscle fibers for explosive strength, or ability to ‘block out’ discomfort.

Intuitively, it makes sense why there is a positive correlation: The brain is the most metabolically demanding organ, and a higher IQ comes with increased calorie demands for the brain. During times of scarcity or famine, you want energy to be conserved. For most of human history–up through the 20th century–life was defined by scarcity, favoring metabolically-efficient brains and bodies. Only recently has food become so abundant that obesity has emerged as a widespread problem. But now, with the rise of AI, the problem is that humans may not be smart enough to contain the very threat they unleashed (although I am more optimistic about AI).

Overall, true, poor life choices play a role in obesity, especially in regard to SNAP recipients, who seem especially vulnerable to obesity, but the role of biology (e.g. IQ, race, metabolism) cannot be dismissed either. This framework may also help reconcile anecdotal observations noted earlier: highly educated, high-IQ tech workers often maintain relatively low body weight despite poor diets and minimal exercise. What looks like a purely moral or lifestyle failure among the poor may instead reflect deeper biological differences that are rarely acknowledged in public discourse.