Public Policy Decisions And The Influence Of Dangerous Data [Opinion]
Over the past year, a series of actions by EPA have shown an agencywide outlook that does not rely on solid science but appears to be bending to popular opinion. In the nutrition world, reliance on popular data that is less robust has caused confusion among consumers, as experts first recommended a low-fat diet and are now backpedaling.
As vegetable growers, you know that scientific data on soil, nutrients, water efficiency, and growth plays a critical role in healthy crop production and output. Scientific data also should be the basis for deciding when to approve new pesticides, alter their indicated uses, or remove them from the market. However, the type of data being used for influential decisions by EPA is a cause for concern for growers of vegetables and is an issue the National Potato Council takes seriously.
How Studies Differ
First, it is important to understand the differences in types of research studies and the data provided as they affect your business and policy decisions made by the government. Epidemiology (Epi) studies, also known as observational studies, are used to examine what risk factors (or exposures) are associated with an increased or decreased risk that a person will develop a disease. They rely on data collection via recall methods or via surveys/interviews.
On the other end of the spectrum are laboratory and clinical studies, which can be done by directly collecting cell samples from live animal or human subjects. A clinical trial is any research study that prospectively assigns human participants or groups of humans to one or more health-related interventions to evaluate the effects on health outcomes. Clinical observations are the gold standard in determining causality. An Epi study shows only an association and the observations relate primarily to groups of people.
In the past few years, Epi studies have been the basis for associating potato intake with certain health problems like diabetes and obesity. These studies are observational and do not actively involve a control group and other clinical measures, and they often get misinterpreted by news outlets who need big headlines. When the results are sensationalized and applied too broadly, the studies are publicly given more significance than is scientifically justified.
Relying largely on Epi data is troublesome as it does not carry the weight of studies specifically designed to look at clinical effects. Once clinical data is available, dietary advice is likely to change, which confuses consumers and creates conflicting messages.
Growers should be aware they are directly affected by Epi data when EPA evaluates insecticides for their effect(s) on human health. In a case where EPA is seeking to revoke the tolerances for an organophosphate product, one or two Epi studies are being used to supplant the findings of hundreds of animal clinical studies that supported the safety of the product. This could lead to the removal of the product from the market. To make matters worse, in this example, the raw data from the Epi studies is not available for review by the scientific community.
For growers, it could mean one less tool to combat crop damage when a pesticide is banned without a credible scientific review. For consumers, it can mean a more limited food supply and higher prices.
A Rush To Judgment
In a related move, EPA released the endangered species effects determination for three chemicals in May, including chlorpyrifos, and opened the docket for public comment. The comment deadline was short, ignoring the fact that accompanying documents requiring comment included more than 1,200 pages of text. This suggests EPA is rushing through the regulatory process without giving stakeholders enough time to review and without properly weighing the huge amount of data. Again, this is a cause for concern.
NPC has gone on record regarding the need for sound scientific principles in the regulatory process. When clinical studies are available, they should be given priority by federal agencies, policy review panels, and government experts. Just as solid data leads to a better crop, it leads to the best decision-making when changing public policy.