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June 12, 2019

The genetics of obesity is about the environment

Filed under: Health,Obesity — Razib Khan @ 11:06 pm
An American classic

In the 1960s the average American man weighed 166 pounds. Today, the average American man weighs 195 pounds. In the 1960s the average American woman weighed 140 pounds. Today, the average American woman weighs 166 pounds. According to the CDC, nearly 40% of Americans age 20 or above are obese. Using the same criteria, less than 5% of Japanese are obese.

Genetically, we know that obesity is more than 50% heritable. That is, within populations, more than 50 percent of the variation of weight is due to the variation of genes. Yet change over a few generations in the distribution of weight implies that genes are not producing a simple outcome here.

Very few genes can explain much of the variation in weight, though on the whole many many genes can explain much of it aggregate.

The FTO gene is one of the major loci implicated in obesity. Those who carry two copies of the “risk” allele are 1.67 times more likely to be obese and are on average 7 pounds heavier than those who carry no copies of the risk allele (those who carry a single copy are 3 pounds heavier, on average). This is not trivial, but neither is it that big of a deal.

Rather, obesity is a highly polygenic trait when it comes to how genetics impacts weight.

There are innumerable genetic factors, some of them implicated in metabolism, while others have to do with satiety and impulse control. This also explains why obesity has varied so much across generations (in the United States) and today varies so much between nations: genes only express themselves in a particular environmental context. There is a “norm of reaction” in a particular environment so that the same genetic profile can result in very different outcomes.

A “Philadelphia Cheesesteak”

Many health professionals argue that the American diet and lifestyle today is very “obesogenic.” Classic 20th-century American foods are often rich in fats, sugars, and processed carbohydrates, which deliver huge servings of calories in massive doses. Calorie density is a feature, not a bug. Extremely palatable processed foods were the end result of an extremely productive agricultural and industrial system.

Meanwhile, whereas 40% of Americans were farmers in 1900, only 2% were in the year 2000. Instead of work that requires physical activity, more and more Americans are office dwellers.

In a world where everyone walked everywhere, daily life was consumed by physical activity, and famine was a constant threat. Latent genetic variation that might result in differences in susceptibility to obesity would not be particularly relevant.

Americans today live in a world where very little of their income goes to food, and calories are in surplus.

Modern agriculture has escaped the “Malthusian trap”

Genetic risk factors in obesity become noticeable in an environment where obesity is common. Historically, the modern period has been an aberration, as humans have escaped the “Malthusian trap,” growing more and more food, while family sizes have decreased. In other words, only in the past century or so in much of the world has the question of the “heritability” of obesity become something that could have been a question in the first place.

Obesity is correlated with many other issues that impact both mortality and morbidity. The past several decades of caloric plentitude and a shift away from manual labor have been beneficial on the whole to human life expectancy and well-being. Famine has become rarer and rarer. But life is often about tradeoffs and as the threat of malnutrition has faded, so the downsides of excess calories have come to the fore.

In this obesogenic environment, genetics can help predict those who are at particular risk for obesity. But genetics is not a solution in any way for the rise of obesity in developed societies, because that rise is due to conditions of the environment.

The genetics of obesity is about the environment was originally published in Insitome on Medium, where people are continuing the conversation by highlighting and responding to this story.

The Insight Show Notes — Season 2, Episode 31: Obesity & Genetic Prediction

Filed under: cardiology,Genetics,Health,Obesity — Razib Khan @ 3:13 pm

The Insight Show Notes — Season 2, Episode 31: Obesity & Genetic Prediction

This week on The Insight (Apple Podcasts, Spotify, Stitcher, and Google Podcasts) Razib talks to Dr. Amit Khera, a cardiologist, and geneticist. We talk about the relationship of genetics to obesity, and the advance of polygenic risk prediction models.

About 30% of Americans are obese, which is defined by a body-mass-index above 30. A further 30% are overweight. Obesity is strongly correlated with a variety of diseases, such as arteriosclerosis and late-onset diabetes. It is also highly heritable, meaning that most of the variation in the American population in the trait is due to variation in the genes. This does not mean that it is a deterministic trait, where certain genes guarantee a particular outcome.

Rather, obesity is the outcome of a host of causes, with the genetic impact being due to many loci.

Only a few genes, such as FTO, actually have a major effect. That means that there are no “fat genes” for most individuals. Rather, there is a wide range of risk factors which lead to obesity. A new paper, with the lead author being Dr. Khera, aims to predict individuals at particularly high risk, Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood.

Though the predictions are modest in consequence for most people, they are highly informative at the extremes. Individuals who are tagged as at high risk for obesity are many times more likely to actually be very obese.

That being said, there is a fair amount of work that polygenic risk scores are highly sensitive to other variables. Though obesity is very heritable, obviously environmental context matters. Americans as a whole have gotten much more obese over the past 50 years despite no change in the underlying genetics.

The Insight Show Notes — Season 2, Episode 31: Obesity & Genetic Prediction was originally published in Insitome on Medium, where people are continuing the conversation by highlighting and responding to this story.

April 19, 2018

Brown fat, the bad kind

Filed under: Obesity,science — Razib Khan @ 2:50 pm

Unless you have been hiding under a rock you know that people of South Asian are at more risk for metabolic disease than is the norm. More concretely we tend toward “skinny fat.”

My current BMI 24. By normal calculators I’m normal weight (barely), because the cut-off is 25. But for South Asian we should be worried if we’re above 23.

There is the caveat that muscle is heavier, so one shouldn’t take BMI literally, as opposed to seriously. You know if you have too much visceral fat, you don’t need to weight yourself. The phenomenon of brown guys with big bellies due to years of self-indulgence is a thing. And excess weight among South Asians who reach a certain affluence level seems a thing the world over.

So here’s a question: for those of you who have managed to keep the weight off and stay trim, how do you do it? Exercise? Diet? Both?

September 1, 2012

The educated and conservative think fatness is a choice

Filed under: Data Analysis,Obesity — Razib Khan @ 8:17 pm

After the post on fatness and homophobia I decided to query the GSS on the extent to which people think that fatness has a strong biological element, similar to homosexuality. There’s a variable, GENENVO1. It asks:

Character, personality, and many types of behavior are influenced both by the genes people inherit from their parents and by what they learn and experience as they grow up. For each of the following descriptions, we would like you to indicate what percent of the person’s behavior you believe is influenced by the genes they inherit, and what percent is influenced by their learning and experience and other aspects of their environment. The boxes on handcard D1 are arranged so that the first box on the LEFT (which is numbered 1) represents 100% genetic influence (and 0% environment). The next box (numbered 2) represents 95% genes (and 5% environment), and so on. The RIGHTMOST box (numbered 21) represents 100% environmental influence (and no genetic influence). After each description, please type the number of the box that comes closest to your answer. Please use the numbered scale on handcard D1 to indicate, FOR EACH OF THE BEHAVIORS DESCRIBED, what percent of the person’s behavior ...

May 16, 2011

The Atlantic features “headless fattie”

Filed under: Genetics,Genomics,Obesity — Razib Khan @ 12:33 pm

I was browsing the front page of The Atlantic and I noticed that it featured a “headless fattie.” This is the standard illustration of obese people in the American media which omits their heads, and tends to focus on their mid-section. You can read about them here. As obesity becomes normal in the United States it is interesting to see how the media is trying to grapple with the topic, and how it illustrates obese people. I found the tensions at the heart of the recent Village Voice piece, Guys Who Like Fat Chicks, fascinating.

If you’ve been to Manhattan you’ll note a distinct paucity of fat folk, let alone ‘fat chicks,’ so the whole piece tends to veer between explicit identity politics consciousness raising and implicit ‘freak show.’ On the one hand many New Yorkers are proud of the fact that because they walk everywhere there’s a norm of a relatively slim physique which would not be typical in much of the American “Heartland.” And yet the fat acceptance movement pretty clearly hooks into the natural sympathy of many in cosmopolitan Lefty circles for identity politics aimed ...

March 2, 2011

Fat China!

Filed under: Fat,Health,Obesity — Razib Khan @ 8:56 pm

Paul French talks about his new book, Fat China: How Expanding Waistlines are Changing a Nation. And rest assured, this is one measure by which America is still #1 in relation to China….

January 14, 2010

Levelling off of the “Obesity Epidemic”?

Filed under: Obesity — Razib @ 12:03 am

There’s a lot of media buzz right now about a new report in JAMA on the empirical trends on prevalence of obesity in the United States. You can read the whole paper here (too many tables, not enough graphs). Interestingly, like George W. Bush it seems that Harry Reid is prejudiced against the overweight. The data in the paper above strongly implies that anti-fat bigotry is going to have disparate impact.

November 29, 2009

Are over-leveraged counties seeing an increase in food stamp usage?

Filed under: data,Diabetes,Food stamps,Obesity — Razib @ 11:33 am

Since The New York Times put up the csv file which they used to generate their maps of food stamp usage, I thought I’d look at the data a little closer. In particular, look at this graphic of change in food stamp usage by county (dark equals more usage):

I was curious about this part from the story below::

While use is greatest where poverty runs deep, the growth has been especially swift in once-prosperous places hit by the housing bust. There are about 50 small counties and a dozen sizable ones where the rolls have doubled in the last two years. In another 205 counties, they have risen by at least two-thirds. These places with soaring rolls include populous Riverside County, Calif., most of greater Phoenix and Las Vegas, a ring of affluent Atlanta suburbs, and a 150-mile stretch of southwest Florida from Bradenton to the Everglades.

Thanks to the Census I happen to have 2007 housing value and household income data. Also though it would be interesting to compare with obesity and diabetes rates. Scatterplots & correlations (r) below.

It does indeed seem that food stamp usage has been increasing in higher income and property value counties. The Census data I used above were collected between 2005-2007, during the height of the late great property bubble. But when I took the ratio of property value by income as a rough proxy for being over-leveraged it didn’t seem to add much.

When I took the partial correlation of home value and increase in food stamp usage controlling for income, it was only 0.11. Here are some other correlations controlling for income:

% on food stamps – obesity = 0.33
% on food stamps – diabetes = 0.44
% of whites on food stamps – white diabetes rates = 0.36
% of whites on food stamps – white obesity rates = -0.05

There’s an obvious correlation between black proportion in a county and food stamp utilization. r = 0.43. So using proportion of blacks as a control:

% on food stamps – obesity = 0.43
% on food stamps – diabetes = 0.51
% on food stamps – white diabetes rates = 0.43
% on food stamps – white obesity rates = 0.06
% on food stamps – median household income = -0.71

It does seem to be correct though that food stamp utilization has been shooting up in more affluent communities. But if it is true that well over 90% of those eligible in places like Missouri are already using food stamps, while only 50% of those eligible in California are, it makes a bit more sense. In wealthier communities likely more people go in and out of eligibility and so never need to make recourse. In contrast, in regions where people are immobile and poverty is chronic there isn’t as much scope to increase the program because most people who are eligible are already on it. That probably explains the triangular geometry of the scatterplot, very low on the affluence latter social services seem to have soaked up all eligible individuals, leaving little room for increase with the recession.

Note: Estimates are white obesity are based on state level variation. Estimates of white diabetes rates are based on national level variation. These two variables need to be appropriately down-weighted in terms of confidence of their accuracy, especially the second.

Update: By coincidence, a reader noted this similarity of maps this morning:

November 25, 2009

Maps of diabetes & obesity

Filed under: Obesity — Razib @ 12:35 pm

Hope readers have a happy Thanksgiving. I assume this is also a day when you’re not going to think too much about your diet and eat what you want to eat. But I thought this map on diabetes and obesity for those age 20 and up was interesting. These are estimates, which I think explains the rather sharp boundaries at state lines (since state level data was probably used to predict county values, see the methods here). To my knowledge the cuisine of the Upper Midwest and New England gets about as much props as that of England (vs. “Southern home cooking”), but hotdish can’t be all that unhealthy? 🙂 H/T Ezra Klein.

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