Hexbyte – Tech News – Ars Technica | A new, eye-wateringly high estimate of the cost of obesity in the US

Hexbyte – Tech News – Ars Technica |

Big numbers —

But the report illustrates how difficult it is to produce a precise figure.


Hexbyte - Tech News - Ars Technica | The total cost includes lost productivity, as well as healthcare costs.
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The total cost includes lost productivity, as well as healthcare costs.

A report released this week puts a surprisingly high figure on the societal cost of obesity in the US: $1.72 trillion annually, or 9.3 percent of GDP. By contrast, the current CDC estimates are in the region of $150 billion, less than one tenth as high.

By far the biggest chunk of that $1.72 trillion is the $1.24 trillion chunk attributed to the “indirect” costs of obesity: the “work absences, lost wages, and reduced economic productivity for the individuals suffering from the conditions and their family caregivers,” the report explains. That is, the bulk comes from costs other than healthcare spending. The estimate for healthcare spending—$480.7 billion annually—is somewhat higher than a range of estimates in reviews of the literature, which hover around $150 to $300 billion, but are still on the same scale.

Estimates like these can vary substantially because of the different methods used in calculating them. For example, a review from 2017 catalogues the different obesity-related diseases that were included in various studies across different countries; respiratory disorders and musculo-skeletal disorders make an appearance in some but not others. A 2016 meta-analysis describes a similarly wide range in how medical costs are calculated.

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The new report was published by the Milken Institute, a think tank that aims to “increase global prosperity by… widen[ing] access to capital, creat[ing] jobs, and improv[ing] health.” That means that, while the report leans heavily on the academic literature, it hasn’t been scrutinized through the process of scientific peer review and doesn’t have the same obligations as a scientific paper to publish the details of its workings.

To reach their estimate, public health economist Hugh Waters and health research analyst Marlon Graf gathered data on a range of chronic health conditions. That range included obvious culprits like stroke and Type 2 diabetes as well as conditions like chronic back pain and liver cancer. They used CDC data to establish how common these diseases are in the US.

Next, they calculated how much of this prevalence could be attributed to obesity. Obviously, it would be insane to consider every case of liver cancer to be the result of obesity, even though obesity is linked to a higher risk of various cancers. So, for instance, to work out what proportion of the total prevalence of liver cancer could be attributed to obesity, Waters and Graf looked at how much higher the risk of liver cancer is for someone with obesity compared to someone without obesity, and they extrapolated that to the overall prevalence numbers.

The data on costs came from a few different sources—a national survey that includes a household survey, along with data from medical insurance, the CDC, and various academic sources. These sources cover both the direct medical costs and the indirect costs of each condition; for instance

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