America has a current and ongoing obesity epidemic. Some ethnicities are more likely to be obese or overweight than others due to lower intelligence which means a lack of ability to delay gratification, lack of ability to think into the future, lower funds which translates to eating more refined carbohydrates which means more blood glucose spikes which then leads to obesity as I will show. Insulin has a causal relationship with obesity so those who lack funds to buy healthier food then turn to refined foods high in carbohydrates as they are cheaper and more abundant in low-income neighborhoods.
Adult obesity rate by State (top 5) is: 1) Louisiana (36.2 percent), 2) Alabama (35.6), West Virginia (35.6), and Mississippi (35.6), and 5) Kentucky (34.6) with the 5 least obese States being 51) Colorado (20.2), 49) Hawaii (20.7), 48) Montana (23.6), 47) California (23.2), and 46) Massachusetts (24.3). Notice how the States with higher rates of obesity are in the South and the States with the lower rates are in the North, give or take. The average IQ for these States as follows: Lousiana: 95.3, Alabama: 95.7, West Virginia 98.7, Mississippi 94.2 (lowest IQ State in the country, largest black population at 37 percent), and Kentucky at 99.4. The average IQ for those States is 96.66. The average IQs for the States with the lowest obesity rates are: Colorado 101.6, Hawaii 95.6, Montana 103.4, California 95.5, and Massachusets 104.3 (highest IQ State). The average for these States being 100.08. So there is a 4 point IQ difference between the top 5 States with the highest and lowest percentage of obese people, which goes with the North/South gradient of higher IQ people living in the North and lower IQ people living in the South. Back in 2014, a California real estate group took 500,000 Tweets using a computer algorithm and estimated intelligence based on spelling, grammar, and word choice and found a difference in State by State intelligence. Notice how the further North you go the higher the average intelligence is, which is then correlated with the obesity levels in that State.
With poverty rates by State, we can see how the States in the South have less intelligent people in them which then correlates to the amount of obesity in the State. Though, there are some anomalies. West Virginia and Kentucky have a super majority of whites. This is easily explained by the fact that less intelligent whites live in those States, and since both the poverty rates and obesity rates are high, it follows that the State will be less intelligent than States that have more intelligent people and less obesity.
It is known that intelligence is correlated with obesity at around -.25 (Kanazawa, 2014). The negative correlation between intelligence and obesity means that they are inversely related so, on average, one with higher intelligence has less of a chance of being obese than one with lower intelligence. The States with the lowest IQ people having those with the highest BMIs corroborates this. In America, obesity rates by ethnicity are as follows: 67.3% for whites, 75.6% for blacks, and 77.9% for ‘Hispanics’.
Now that we know the average intelligence rates by State, the percentage of obese by State and the demographics by State, we can get into why obesity rates correlate with intelligence and race.
Diaz et al (2005) showed that minority populations are more likely to be affected by diabetes mellitus which may be due to less healthy diets and/or genetic factors. Using the National Health and Nutrition Survey for 1999-2000, they analyzed overweight, healthy adults, calculating dietary intake variables and insulin sensitivity by ethnicity. They characterized insulin resistance with fasted insulin, as those who are more likely to become insulin resistant have higher fasted insulin levels (levels taken after waking, with the subject being told not to eat the night before as to get a better reading of fasted insulin levels). Non-‘Hispanic’ whites had higher energy and fat intake while ‘Hispanics’ had higher carb intake with blacks having lower fiber intake. Blacks and ‘Hispanics’ were more likely to have lower insulin sensitivity. However, ‘Hispanics’ were more likely to have lower insulin sensitivity even after controlling for diet, showing that metabolic differences exist between ethnicities that affect carbohydrate metabolism which leads to higher rates of diabetes in those populations.
Drewnowski and Specter (2004) showed that 1) the highest rates of obesity are found in populations with the lowest incomes and education (correlated with IQ), 2) an inverse relationship between energy density and energy cost, 3) sweets and fats have higher energy density and are more palatable (food scientists work feverishly in labs to find out different combinations of foods to make them more palatable so we will eat more of them), and 4) poverty and food insecurity are associated with lower food expenditures, lower fruit and vegetable intake, and lower-quality diet. All of these data points show that those who are poor are more likely to be obese due to more energy-dense food being cheaper and fats and sugars being more palatable.
Now that I’ve shown the relationship between race and IQ by state, obesity rates by state, insulin sensitivity by race, and that those in poverty are more likely to be obese, I can now talk about the actual CAUSE of obesity: insulin.
The conventional wisdom is that if you consume more kcal than you expend, you will gain weight, whereas if you consume less than your daily needs you will lose weight. This has been unchallenged for 50 years. Also known as Calories In and Calories Out (CICO), this mantra “eat less and move more!!!” has been bleated over and over with horrendous results. The CICO model only concerns itself with calories and not insulin which is a causal factor in obesity.
In this study, participants in the basal insulin group which received the lowest average insulin dose gained the least average amount of weight at 4.2 pounds. Those on prandial insulin gained the most weight at 12.5 pounds. The intermediate group gained 10.3 pounds. More insulin, more weight gain. Moderate insulin, moderate weight gain. Low insulin, low weight gain.
Researchers compared a standard dose of insulin to tightly control blood sugars in type 1 diabetic patients. At the end of the 6 years, the study proved that intensive control of blood sugars resulted in fewer complications for those patients.
Though, in the high dose group, they gained on average 9.8 pounds more than those in the standard group.
More than 30 percent experienced major weight gain! Prior to the study, both groups were equal in weight. But the only difference was the amount of insulin administered. Were the ones given high levels of insulin all of a sudden more lazy? Were those who gained weight suddenly lacking in willpower? Were they lazier before the study? We’re they more gluttonous? No, no, and no!!
Finally, Henry et al (1993) took Type II diabetics and started them off with no insulin. They went from 0 units of insulin a day to 100 units at 6 months. As higher rates of insulin were administered, weight rose in the subjects. Insulin was given, people gained weight. A direct causal relationship (see figure above). However, what’s interesting about this study is that the researchers measured the amount of kcal ingested, the number of kcal ingested was reduced to 300 per day. Even as they took in less kcal, they gained 20 pounds! What’s going on here? Well, insulin is being administered and if you know anything about insulin it’s one of the hormones in the body that tells the body to either store fat or not burn it for energy. So what is occurring is the body is ramping down its metabolism in order for the subject to store more fat due to the exogenous insulin administered. Their TDEE dropped to about 1400 kcal, while they should have been losing weight on 1700 kcal! The CICO model predicts they should have lost weight, however, adaptive thermogenesis, better known as metabolic slow down, occurred which dropped the TDEE in order for the body to gain fat, as insulin directly causes obesity by signaling the body to store fat, so the body drops its metabolism in an attempt to do so.
Putting this all together, blacks and ‘Hispanics’ are more likely to be in poverty, have lower intelligence, and have higher rates of obesity and diabetes. Furthermore, blacks are more likely to have metabolic diseases (adaptive thermogenesis aka metabolic slowdown is a metabolic disease) which are related with obesity due to their muscle fiber typing which leads to lower maximal aerobic capacity (less blood and oxygen get around the body). Type II skeletal muscle fibers’ metabolic profile contributes to lower average aerobic capacity in blacks. It also is related to cardiometabolic diseases, in my opinion because they don’t have the muscle fiber typing to run long distances, thus increasing their aerobic capacity and VO2 max.
Due to the diets they consume, which, due to being in poverty and having lower intelligence, they consume more carbohydrates than whites, which jacks their blood glucose levels up and the body then releases insulin to drive the levels glucose in the body down. As insulin levels are spiked, the body becomes insulin resistant due to the low-quality diet. Over time, even a change in diet won’t fix the insulin resistance in the body. This is because since the body is insulin resistant it created more insulin which causes insulin resistance, a vicious cycle.
Poverty, intelligence and race both correlate with obesity, with the main factor being lower intelligence. Since those with lower IQs have a lack of foresight into the future, as well as a lower ability to delay gratification which also correlates with obesity, they cannot resist low-quality, high-carb food the same way one with a higher IQ can. This is seen with the Diaz et al study I linked, showing that whites have higher levels of fat intake, which means lower levels of carbohydrate intake in comparison to blacks and ‘Hispanics’. As I’ve shown, those in poverty (code word for low intelligence) ingest more refined carbohydrates, they have higher levels of obesity due to the constant spiking of their insulin, as I have shown with the 3 aforementioned studies. Since blacks and ‘Hispanics’ have lower levels of intelligence, they have lower levels of income which they then can only afford cheap, refined carbs. This leads to insulin being constantly spiked, and with how Americans eat nowadays (6 times a day, 3 meals and snacks in between), insulin is being spiked constantly with it only dipping down as the body goes into the fasted state while sleeping. This is why these populations are more likely to be obese, because they spike their insulin more. The main factor here, of course, is intelligence.
Another non-CICO cause for obesity is exposure to BPA in the womb. Researchers carried out BPA testing in three differing subjects: 375 babies invitro, (3rd trimester) children aged 3 (n=408) and aged 5 (n=518) (Hoepner, et al, 2016). They measured the children’s bodies as well as measuring body fat levels with bioelectrical impedance scales.Prenatal urinary BPA was positively associated with waist circumference as well as fat mass index, which was sex-specific. When analyzed separately, it was found that there were no associated outcomes in body fat for boys (however it does have an effect on testosterone), but there was for girls (this has to do with early onset puberty as well). They found that after controlling for SES and other environmental factors there was a positive correlation with fat mass index – a measure of body fat mass adjusted for height, body fat percentage and waist circumference. The researchers say that since there was no correlation between BPA and increased obesity, that prenatal exposure to BPA indicates greater vulnerability in that period. The sample was of blacks and Dominicans from New York City. Whites drink less bottled water, which has higher levels of BPA. Blacks and ‘Hispanics’ consume more, and thus have higher levels of obesity.
In conclusion, blacks and ‘Hispanics’ are more likely to be in poverty, have lower intelligence, higher rates of obesity and lower incomes. Due to lower incomes, cheap, refined carbohydrates is what they can afford in bulk as that’s mostly what’s around poor neighborhoods. Ingesting refined carbohydrates more often consistently jacks up blood glucose which the body then releases insulin to lower the levels. Over time, insulin resistance occurs, which then leads to obesity. As I’ve shown, there is a direct causal relationship between the amount of insulin administered and weight gain. With the aforementioned factors with these two populations, we can see how the hormonal theory of obesity fits in perfectly with what we know about these ethnic groups and the obesity rates within them. Since people in poverty gravitate more towards cheap and refined carbohydrates, they’re constantly spiking their insulin which, over time, leads to insulin resistance and obesity.