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Yesterday I tweeted out Obesity Rate for Young Children Plummets 43% in a Decade. This is a big deal, and many people retweeted it. Here’s the summary in The New York Times:

But the figures on Tuesday showed a sharp fall in obesity rates among all 2- to 5-year-olds, offering the first clear evidence that America’s youngest children have turned a corner in the obesity epidemic. About 8 percent of 2- to 5-year-olds were obese in 2012, down from 14 percent in 2004.

They helpfully link to the paper in The Journal of the American Medical Association, Prevalence of Childhood and Adult Obesity in the United States, 2011-2012. And actually, if you read the paper the authors themselves seem very unsure about the robustness of this specific result. I quote from the paper:

…Tests for differences by age in children were evaluated with the following comparisons: aged 2 to 5 vs 6 to 11 years, 2 to 5 vs 12 to 19 years, and 6 to 11 vs 12 to 19 years. Similarly, in adults comparisons were made between aged 20 to 39 and 40 to 59 years, 20 to 39 and 60 years or older, and 40 to 59 and 60 years or older. P values for test results are shown in the text but not the tables. Adjustments were not made for multiple comparisons.

…Similarly, there was no significant change in obesity prevalence among adults between 2003-2004 and 2011-2012. In subgroup analyses, the prevalence of obesity among children aged 2 to 5 years decreased from 14% in 2003-2004 to just over 8% in 2011-2012, and the prevalence increased in women aged 60 years and older, from 31.5% to more than 38%. Because these age subgroup analyses and tests for significance did not adjust for multiple comparisons, these results should be interpreted with caution.

In the current analysis, trend tests were conducted on different age groups. When multiple statistical tests are undertaken, by chance some tests will be statistically significant (eg, 5% of the time using α of .05). In some cases, adjustments are made to account for these multiple comparisons, and a P value lower than .05 is used to determine statistical significance. In the current analysis, adjustments were not made for multiple comparisons, but the P value is presented.

The p-value here is 0.03 for the difference in question. That passes the conventional threshold of significance (0.05), but it is close enough to the border that I’m quite suspicious. Here is the full conclusion of the paper:

Overall, there have been no significant changes in obesity prevalence in youth or adults between 2003-2004 and 2011-2012. Obesity prevalence remains high and thus it is important to continue surveillance.

Granted, these may turn out to be real true results. And the age class that showed a decline in obesity is definitely one we should focus on. But public health is a serious matter, and therefore we shouldn’t get ahead of ourselves.

One hypothesis that presents itself in regards to this paper is that a reviewer asked explicitly about the multiple comparisons problem. The authors acknowledged the problem, without actually checking to see if the results hold after a correction, and then the editor let the paper through. Of course this is just a model. I haven’t tested it, so can’t even offer up a p-value, even if I was a frequentist.

Note: The raw data is here.

• Category: Science • Tags: Health, Medicine, Obesity 
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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 you think is influenced by the genes they inherit, and what percent is influenced by their learning and experience. After each question, type the number of the box that comes closest to your answer. Remember, the higher the number, the more you think the behavior is influenced by learning and experience; the lower the number, the more you think it is influenced by genes. Carol is a substantially overweight White woman. She has lost weight in the past but always gains it back again.

Yes, the question itself is somewhat scientifically incoherent. Heritability doesn’t really work this way, but in the colloquial sense it is not an unreasonable question to ask, as it gauges real sentiment. Because the response are in five point increments, I combined the intervals 0 to 25% and 75 to 100%, and left the middle as a separate category. I crossed that with a host of demographics, and also re-ran the analysis for non-Hispanic whites only.

Before I report the results I’ll stipulate a few things (this might preempt me having to ban people who sincerely leave long, but unpleasant, comments). I accept that weight is substantially heritable, but I do not believe that the levels of obesity that we see in the United State are inevitable. But, I do also believe that there is a “moral panic” of sorts about obesity in the United States. Much of the attack on obesity which is grounded in real concerns about health also does rely upon the genuine loathing and disgust toward fat people which is widespread in American society. Additionally, there is a class dimension here, insofar as in the United States being grossly obese is more emblematic of the lower orders. All that being said, I think it is important to acknowledge that the vast majority of obese people would be happier, and live more fulfilled lives, if they weren’t obese. Though this doesn’t entail that I agree with criminalizing obesity, it does mean that I think that the “fat acceptance movement” is misguided. Rather than acceptance of fat, people need to be more generally civilized toward a level of inter-personal kindness which would diminish a whole host of cruelties. We don’t need to “liberate” fat people. We just need to “not be dicks.”


Being overweight is….
100 to 75% genes 70 to 30% genes 25 to 0% genes
Respondent’s weight
AVERAGE 18 48 34
18-25 20 48 32
26-40 19 45 35
41-65 17 46 37
66- 18 49 34
MALE 18 45 36
FEMALE 18 47 34
WHITE 16 48 36
BLACK 27 39 34
HISPANIC 26 40 34
Socioeconomic index
Bottom 1/3 25 41 34
Middle 1/3 17 47 36
Top 1/3 14 50 35
<HIGH SCHOOL 30 40 30
HIGH SCHOOL 20 43 37
BACHELOR 14 52 34
GRADUATE 8 57 35
Income indexed to 1986 dollars
<$20 23 44 33
$20-40 20 47 34
$40-60 10 49 41
$60-80 15 54 31
$120-140 15 46 39
Liberal 28 43 29
Moderate 17 52 30
Conservative 18 44 38
Non-Hispanic whites
Respondent’s weight
AVERAGE 15 50 35
18-25 16 55 28
26-40 15 48 37
41-65 15 48 37
66- 17 50 33
MALE 16 48 37
FEMALE 15 50 34
Socioeconomic index
Bottom 1/3 22 43 35
Middle 1/3 15 48 36
Top 1/3 13 53 35
<HIGH SCHOOL 28 44 29
HIGH SCHOOL 17 46 37
BACHELOR 11 53 36
GRADUATE 8 59 33
Income indexed to 1986 dollars
<$20 18 49 32
$20-40 17 48 35
$40-60 8 50 41
$60-80 16 55 29
$120-140 14 46 40
Liberal 22 46 32
Moderate 16 54 30
Conservative 15 46 39

Out of curiosity I ran a linear regression with the variable not recombined into three categories (so the full 1 to 21 range in outcomes). Basically the only major statistically significant predictors seem to be education and political ideology. The less educated and more liberal tend to think that an individual’s weight is more due to their genes than the more conservative and more educated.

Image credit: Wikipedia

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Data Analysis, Obesity 
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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 to uplift the marginalized. They leverage the same general structure of argument applied to racial and later sexual minorities, attempting to de-pathologize a body type which is currently the focus of great public health concern.

Here’s the paper which triggered the piece in The Atlantic, Identification of an imprinted master trans regulator at the KLF14 locus related to multiple metabolic phenotypes:

Genome-wide association studies have identified many genetic variants associated with complex traits. However, at only a minority of loci have the molecular mechanisms mediating these associations been characterized. In parallel, whereas cis regulatory patterns of gene expression have been extensively explored, the identification of trans regulatory effects in humans has attracted less attention. Here we show that the type 2 diabetes and high-density lipoprotein cholesterol–associated cis-acting expression quantitative trait locus (eQTL) of the maternally expressed transcription factor KLF14 acts as a master trans regulator of adipose gene expression. Expression levels of genes regulated by this trans-eQTL are highly correlated with concurrently measured metabolic traits, and a subset of the trans-regulated genes harbor variants directly associated with metabolic phenotypes. This trans-eQTL network provides a mechanistic understanding of the effect of the KLF14 locus on metabolic disease risk and offers a potential model for other complex traits.

Basically it looks like they found a genomic region which has a global regulatory effect on a lot of genes, and therefore the metabolic tendencies of fat tissue. Not trivial. I can see why The Atlantic headline is “British Scientists Find the Fat Gene.” But taking into account the magnitude of the obesity problem in the United States I wish that the media wouldn’t label this in such an easily misinterpreted manner. Skimming over the statistics for example I don’t get a sense that most of the variance in the population of obesity is due to the variation at this locus. Though someone can correct me.

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Genetics, Genomics, Obesity 
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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….

(Republished from Discover/GNXP by permission of author or representative)
• Category: Science • Tags: Health, Obesity 
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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.

(Republished from by permission of author or representative)
• Category: Science • Tags: Obesity 
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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:

(Republished from by permission of author or representative)
• Category: Science • Tags: Data, Diabetes, Obesity 
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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.

(Republished from by permission of author or representative)
• Category: Science • Tags: Obesity 
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Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at"