Thursday, June 20, 2013

GM Oh No! Part 1.5 of 3: Pig health considerations

A blog of Bridge Environment, updated most Thursdays

This entry is a follow up to the first in a three-part series about genetically modified organisms (GMOs)

Which technological creations do pigs fear more,
GMO feed or mutant super birds?
Last week, I defined, put into historical context, and considered the human health effects of genetically modified (GM) food items, also known as GMOs. While promising to explore environmental and political/economic considerations in future blogs, I concluded that human health concerns were more modest than critics would have you believe, but that there is potential value in conducting long-term testing of food varieties, GM or otherwise, that differ in substantial ways from their predecessors. As I will describe in the political/economic post, there may also be reasons to worry about financial and political influences on the approval process.

About the same time as that blog posting, a scientific study was published on the health of pigs which ate a GM diet (Carman et al. 2013). The authors used what one might call a shotgun approach. Instead of a targeted study with a specific concern in mind, they examined many anatomical and biochemical characteristics of 84 slaughtered pigs fed a GMO diet and 84 fed an equivalent non-GMO diet. Out of the many characteristics they tested, they found differences they described as statistically significant for two characteristics: uterine size and the rate of severe stomach inflammation. Though there have been a few balanced blog posts and media reports about this study, the majority used headlines such as “GMO feed turns pig stomachs to mush!,” perhaps not surprising for a source called Natural News. But MSN Now ran “GMO feed wreaked havoc on pigs’ stomachs.” If general media reports are to be believed, this study confirmed our fears: GMO foods do horrible things to our health.

Is it true? Was my advice last week off-base? Let me start by reassuring you that the study does not change my conclusions at all. Here is why.

First, let’s consider uteruses. According to the authors, they were 25% larger in pigs fed GMO corn and soy (median 0.105% of total body weight versus 0.086% body weight) and this difference was stastically different at the 2.5% level (known as a p-value, where p stands for probability). However, their claim is complicated and, in some cases misleading, due to several factors:
  • the math: as reported in their tables, uteruses of GMO-fed pigs were 22% larger than those of non-GMO-fed pigs, but this may be a typo since the results from the table do not match what is reported in the text;
  • attrition: several pigs died in the experiment (11 non-GM-fed pigs and 12 GM-fed pigs) and one non-GM-fed female pig failed to develop a uterus at all, so there may be a bias based on which pigs developed and survived until the end of the experiment; and
  • the health significance: we have no understanding of whether larger uteruses for pigs at this stage in development is a good or bad thing; in fact GMO-fed pigs were slightly larger at slaughter so the difference may simply indicate faster sexual maturity.
The authors’ claim of statistical significance raises even more concerns. Scientists typically only make strong claims about results if observed differences have a 5% or smaller chance of occurring due to random variation. Scientists picked the 5% p-value threshold because of a desire to maintain high standards prior to claiming that an observed difference is real. Even then, one in twenty times a scientist will report a meaningful finding that was simply due to random differences among similar individuals.

This grey area of scientific proof becomes far murkier when multiple comparisons are made. Because of the shotgun appraoch of this study, where one treatment was conducted and many comparisons were made, we would expect a far greater chance of an observed difference being due to chance than if only one observation had been made. My first real statistics professor referred to such shotgun approaches as p-ing all over the page, and this paper is guilty. For example, they measured eight separate organs from the same set of pigs. In each of those eight comparisons, there would be a 5% chance of mistakenly thinking there was an effect of GMO feed when in fact the difference was random chance. Collectively over the eight comparisons, there would be a 1 in 3 chance1 of thinking at least one organ size difference was attributable to diet when in fact the pigs were essentially the same. To correct for this multiple comparison bias, scientists are supposed to adjust the threshold for considering a result significant. In the case of eight comparisons, the new standard of significance would be 0.64% for each organ, and the authors’ p-value of 2.5% would not be adequate to claim a true difference between the uteruses of GMO- and non-GMO-fed pigs.

Inflamed stomachs were even more problematic than large uteruses. The authors claim that severe inflammation occurred over 2.5 times more often in GM-fed pigs and that the difference at a p-value of 0.4%. However, the authors made 16 separate comparisons of pathological conditions. To correct for the multiple comparisons, they should have adjusted their significance level per condition down to 0.32%. Once again, valid use of statistics would keep them from claiming a true difference. It is even more interesting when we examine the other observed differences between GM-fed and non-GM-fed pigs, many of which were related to the stomach. Whereas GM-fed pigs more often had severe stomach inflammation, they also more commonly had no inflammation, and less often had mild or moderate inflammation. There are statistical tests to compare multiple category data like these, but it is not surprising that the authors failed to use them considering their failure to address multiple comparisons. Had they performed it, such an analysis would have provided ambivalent results because of the fact that GM-fed pigs had higher incidence of stomach health but also of severe inflammation. GM-fed pigs also had lower incidence of stomach erosion, pin-point ulcers, and bleeding ulcers, but higher incidence of frank ulcers (not sure what they are…aren’t all ulcers honest?). GM-fed pigs also had lower incidence of heart, liver, and spleen abnormalitlies. Mind you, none of these differences were statistically significant, either, so all of this analysis should be taken with a very large grain of salt.

What really stands out for me in this study is not the effect of a GM diet, but the condition of all pigs raised commercially for meat production. Over the course of these pigs’ short lifetime (less than six months), more than one in eight died prior to slaughter, even with veterinary treatment. The article reassures us that these death rates are “within expected rates for US commercial piggeries.” Of the survivors, more than 1 in 10 had heart abnormalities, 1 in 5 had abnormal lymph nodes, over half had moderate to severe stomach inflammation, nearly 3 in 5 had pneumonia, and 4 in 5 had stomach erosions. The condition of these animals definitely makes me ponder eating more seafood.

Back to GMO health effects…applying scientific standards for statistical interpretation, this study becomes inconclusive. We could choose to be like the authors and interpret trends in the data that may simply be a result of random chance. This exercise yields a complex picture without any obvious indication that GM-fed pigs were healthier or less healthy than their non-GMO-fed counterparts. Should we dismiss the findings entirely? I don’t think so. Some of those trends may be a result of real effects. However, follow up study would be necessary and should be focused on particular concerns and analyzed correctly. At this point, though, there still is no credible evidence of health effects associated with common GMO food supplies. I maintain my conclusions from last week, and promise to flesh out larger concerns surrounding environmental impacts and political/economic influence over the coming weeks.

News outlets that presented this research otherwise have shown you their lack of respect for understanding science and, purposely or inadvertently, played on our human tendency to panic over uncertainties. You might want to consider better news sources in the future.


For more information, read our other blog posts and visit us at Bridge Environment.

1 If each comparison is treated as significant when the statistics report a 5% chance of mistaking random variation for a true result, then each has a 95% chance of correctly identifying random differences as being just that. To get it correct for eight different comparisons, we have to multiply 0.95 by itself eight times, 0.958 = 0.66. In other words, the likelihood that we correctly eight observed differences as due to random chance is only 66%, leaving a 34% chance…one in three, of seeing at least one false positive.

Friday, June 14, 2013

GM Oh No! Part 1 of 3: Human health considerations

A blog of Bridge Environment, updated most Thursdays

This entry is the first in a three-part series about genetically modified organisms (GMOs)

GMOs: Monsters or unsung superheroes?
Genetically modified (GM) food items prompt one of two reactions. Some people panic, not wanting anything to do with them. The panic reaction has dominated European politics and led to a near-ban on growing (but not importing) GMOs. Other people ignore the issue, preferring to remain untroubled by yet another risk of modern life. The denial reaction has dominated US politics so far, where even efforts to label GMOs have fallen flat. These two reactions should not be surprising: they are our natural human responses to uncertainty. To foster a more rational debate regarding GM foods, we present a three-part series. Today we define the term GM, put GM practices into historical context, and consider human health effects. Next week, we will discuss potential ecological consequences. In two weeks, we will wrap up the series with a discussion of intellectual property, market power, and politics. In general, we will conclude that GMOs pose greater risks than proponents would have you believe, but smaller ones than critics suggest. Rather than ban them outright, we encourage smart regulation along with accurate education. With proper oversight and regulation, GMOs are neither terrible monsters nor superheroes capable of saving us from ourselves.

To start, let’s define GMOs by putting them into historical context. Humans have shaped our food supply throughout history and have, through farming practices, caused purposeful genetic modifications in nearly everything we eat. In large part, these modifications are a result of selective breeding1, whereby people produce the next generation of domesticated plants or animals using prize specimens. Over millennia, selective breeding practices shaped the genes of domesticated grains, vegetables, fruits, meats, and even microbial products like cheese and wine, making them more productive and more desirable to consume. In this way, nearly everything we eat could be considered genetically-modified. However, the GMO term is reserved for a specific method of creating new varieties.

The next big technology for shaping our food supply came in the first half of the 20th century when agricultural scientists began causing mutations in plants by exposing them to radiation or harsh chemicals. The resulting individuals are screened for desirable traits and, in some cases, interbred with existing strains to further improve them. The varieties resulting from these processes are even more genetically-modified than those developed via selective breeding alone, but still do not qualify for the term GMOs.

Instead of relying on mutagenic conditions, true GMOs are developed in a calculated and precise way. Specific properties are sought, appropriate genes are identified in other organisms, and then a GMO is engineered by combining the genes of multiple plants or animals, a process referred to as transgenesis. This process is inspired by transduction. Discovered in the early 1950s, transduction is a natural phenomenon by which certain viruses are capable of incorporating a piece of DNA from one host into their own genome, carrying it to another host, and inserting it into the new host’s DNA. As creepy as this phenomenon sounds, it can be beneficial. Transduction is involved in the rapid evolution of antibiotic resistance in bacteria, for example (good for the bacteria even if it is not for us), and has promise for inserting functional gene copies into cells of people who suffer from genetic disorders. When creating a GMO, scientists transfer DNA using plasmids, which have many similarities with the transduction-capable genetic material of viruses. The scientists’ goal is to create a transgenic superorganism.

In some ways, the creation of GMOs is merely a more controlled version of techniques we have used for millennia. From a policy perspective, what separates this technique is the rapidity and scope of changes that can be made. The rate of change offers both promise and peril. For example, consider AquaAdvantage salmon, also known as the Frankenfish. This GM salmon has been engineered by adding genes from Chinook salmon (Oncorhynchus tshawytscha) and ocean pout (Zoarces americanus) to Atlantic salmon (Salmo salar). The introduced genes allow the engineered salmon to grow twice as fast as existing varieties of farmed Atlantic salmon.

The transgenic nature of GMOs tends to fuel our imagination and make us believe we are eating something contaminated. In reality, GMOs are made with precise and controlled technologies compared to the older radiation- and chemical-based methods. Regardless, the genetic changes are the one major lasting effect of the environment that created new varieties using either of these techniques. If there are health risks, they are most likely going to be from the resulting properties of the food, not the details of its creation.

When it comes to health consequences, GM foods are not particularly different from other varieties humans have developed throughout our history. It is possible that any new variant may have unintentional health effects. The obvious solution to this challenge is testing, which does take place on GMOs prior to human consumption. Testing is capable of identifying major toxic issues quickly, but not as capable of identifying rarer problems like an unusual allergy, or long-term risk for diseases like cancer, which may only manifest in some individuals and only after years of exposure.

GMOs have been in our food supply since the mid-1990s and no human health issues have yet been identified. This result does not mean that GMOs are all safe for human consumption. The fact that they can differ so quickly and dramatically from previous varieties means that GMOs should be subject to additional scrutiny and longer-term testing than, for example, a variety derived from selective breeding. However, we should not see GMOs as somehow wholly distinct. In all cases where a new variety is notably novel, we should consider more extensive and longer-term testing.

The same logic applies to labeling. While labeling seems reasonable from a perspective of informed consumers, producers are legitimately worried that a GMO label would be seen by the public as a hazard warning. Such a warning may be warranted if the public does not have faith in the ability of food regulators to accurately gauge the health risks associated with novel food items. However, such a concern could be applied equally well to food items derived via radiation- or chemical-exposure. If we do label, we should do so based on the novelty of a food and accompany that effort with a public education campaign.

This does not necessarily mean that GMOs are safe, but it does mean that health concerns are less of a factor in regulating GMOs than environmental risks and the influences of monopoly power. They will be the subject of our blog entries in the following two weeks.


For more information, read our other blog posts and visit us at Bridge Environment.

1 Selective breeding is so pervasive and effective that it helped inspire Darwin’s development of evolutionary theory.

Thursday, June 6, 2013

The budget deficit and inter-generational fairness

A blog of Bridge Environment, updated most Thursdays

Not the only way old people are screwing young ones
Last month, I posted a couple of blog entries about the US economy. One highlighted that fiscal stimulus, while most likely a good idea, requires a balanced perspective based on risk management. Another contrasted the typical effectiveness of economists with the ineffectiveness of ecologists at influencing policy, despite similar information gaps and system complexities. Whereas I feel economists do generally succeed and perform well in informing many policy decisions, fiscal stimulus is not the only exception. There has also been a general failure to inform what economists would describe as distributional consequences or, more simply put, fairness.

The current projections of US debt serve as an excellent example where economic analysis on equity is available but generally has not entered into public debate. Much of the facts in the following paragraph come from an information-intensive but ideologically-conservative source, JustFacts. I prefer to avoid ideology, but do appreciate well-researched arguments on either side of an issue.

Our official government debt presently stands at $16.7 trillion. However, this figure does not account for outstanding obligations. If the government were a publicly-traded company, it would be required to include:
  • $7.5 trillion in federal employee retirement benefits, accounts payable, and environmental liabilities.
  • $21.6 trillion in Social Security obligations, above and beyond expected revenues.
  • $27 trillion in Medicare obligations, above and beyond expected revenues.
Using these values and taking into account assets that the government holds (cash, loan holdings, inventories, etc.), the government has a shortfall of $67.7 trillion dollars.

This figure is still not the full story. The government is projected to run ongoing budget deficits, which will add to the debt. On the other hand, the government has created public infrastructure which is worth a substantial amount of money. Neither of these issues is accounted for in the $67.7 trillion dollar figure.

This debt figure is eye-catching and worthy of consideration in its own right, but becomes even more fascinating when we consider its distributional consequences. Let’s consider the winners and losers of three different sources of deficit: excess past spending, Social Security, and Medicare.

Past spending (including commitments to programs like the federal retirement system) makes up about a third of the total deficit figure. Heavy debt is, for the most part, a recent phenomenon. Earlier governments generally ran modest deficits and contributed greatly to the country’s infrastructure and potential for economic growth. Here are a few examples. The Civilian Conservation Corps engineering projects in the 1930s created water supplies and economic opportunities in many parts of the country. The G.I. Bill provided college education to millions of World War II veterans, and a sophisticated work force for the country. The interstate highway system, which began in the 1950s, allowed for efficient movement of people and goods across the country. This sort of project is important to keep in mind when weighing debt because of the long-term value it creates, much like the fact that a family investment in a new business is very different from buying big screen TV.

Our current debt came primarily during the 1980s, 1990s, and past 10 years, when tax cuts were not balanced by spending reductions. This debt did not provide major infrastructure improvements. Instead it funded ongoing discretionary government spending along with weapons development (e.g., the Cold War) and military campaigns (e.g., Iraq, Afghanistan, Iraq again). The benefits from earlier generations’ investments as part of relatively balanced budgets continue to pay off to society at large. The deficit spending of the 1980s, 1990s, and present supported our current economy but may not add much future value. Who are the winners from this debt? The wealthy surely benefited, not only from tax breaks but also from the fact that they have garnered the bulk of recent economic growth. The poor may have broken even: they have seen job opportunities and some key services (e.g., public universities) shrink. On the other hand, they too have received tax breaks/credits, and the lost job opportunities may be more related to cheap unskilled overseas labor alternatives than to U.S. fiscal policy. Future generations definitely lose out since we most likely will pass on this debt without the same level of infrastructure investment of previous generations.

Social Security and Medicare make up the rest of the deficit. These two programs are paid for through payroll taxes and provide benefits once people reach retirement age. Social Security began in 1935, during the Great Depression. The idea of a government health insurance program was debated for decades before Medicare was enacted in 1965, and the end product was scaled back to cover only retirees. Neither program functions as a savings account. Money for current outlays comes from taxes levied on current employees. However, the tax rates for these programs are roughly designed so that an individual’s contributions while working will pay for their expected expenses in retirement. However, the rate calculations are not dynamic, meaning they do not change terribly often. The rates for both programs have been the same since the late 1980s/early 1990s. More importantly, the rates reflect survival rates of retirees at the time. In reality, there have been dramatic increases in life expectancy for Americans since Social Security was enacted. A sizable portion of this increase comes from reduced infant mortality, which does not affect these programs since people who die before they begin to work do not contribute to nor benefit from them. However, life expectancy at age 20 has also steadily improved and continues to do so. In 1940, slightly more than half of 20 year olds lived to reach 65, and those who did typically lived an extra 12 years. Today, about 80 percent of 20 year olds reach 65 and typically live an extra 18 years. As a result, people spend more years in retirement but contribute over the same number of years worked. For Social Security, and to a lesser extent Medicare, we run a bit of a Ponzi scheme. The first entrants had no history of paying taxes to fund these entitlements and so got them at the expense of workers at the time. Because we continue to underestimate longevity while calculating the tax rates, retirees still get more than they paid for at the expense of current workers.

As with any Ponzi scheme, these programs will work well until they finally don’t. Baby Boomers just might be the breaking point. They are no different from retirees that came before them in having underfunded their own public retirement and health insurance. What makes them different is their sheer numbers. Birth rates fell through the early 1900s as a result of industrialization, then spiked following World War II. Whereas the relatively large numbers of babies in the early 20th century were offset by high mortality rates, working-age Baby Boomers are surviving longer than any generation before them. The result is that, whereas large numbers of Boomers contributed funds their retired elders, the ratios are shifting and fewer workers will be supporting more retirees. Given the Ponzi scheme nature of Social Security and Medicare, we will see an extreme burden on the post-Baby Boomers, partly because tax rates were insufficient to bankroll enough savings to support the Baby Boomers in retirement, and partly because the burden of making up the gap will fall on relatively few working adults. Who wins from the resulting deficits? First generation recipients of Social Security and Medicare were the biggest winners since they had not paid into the systems. Generations following them received lesser benefits but still got some. As with any Ponzi scheme, it is the final investors who take the loss. Here we have a choice. We can scale back the scope of these programs by, for example, raising the retirement age or reducing benefits. Doing so would spread the pain out over multiple generations. Or, we can go on our current trajectory, which will leave a much smaller group of Americans to bear the brunt of the costs. 

This issue is not just one of equity. As the debt figures quoted earlier indicate, addressing Social Security and Medicare will get us a long way towards tackling the federal deficit. Doing so would reduce the chances of broader economic stagnation and give the government more flexibility to use tools like stimulus funds to smooth out bumps in our economic performance.


For more information, read our other blog posts and visit us at Bridge Environment.