As of September 12, 2026
Most fruits and vegetables never touch a lab before they reach a grocery cart. A new study asked what happens after they leave it.
In September 2025, a team of researchers published a paper in the International Journal of Hygiene and Environmental Health building something the pesticide-testing world hadn't quite built before: a single cumulative score for how much pesticide exposure a person's produce-eating pattern adds up to, then checked that score against actual urine samples. The paper is Temkin et al., "A cumulative dietary pesticide exposure score based on produce consumption is associated with urinary pesticide biomarkers in a U.S. biomonitoring cohort," DOI 10.1016/j.ijheh.2025.114654.
The method combined two federal data sources. Pesticide residue findings collected by the USDA's Pesticide Data Program, which tests thousands of produce samples a year for hundreds of pesticide compounds, were used to build an exposure score based on what people reported eating. That score was then checked against urinary pesticide biomarker measurements from 1,837 participants in the CDC's National Health and Nutrition Examination Survey, drawn from the 2015-2016 cycle. NHANES collects both dietary questionnaires and biological samples from the same people, which is what made the comparison possible. The biomarkers covered three pesticide classes: organophosphates, pyrethroids, and neonicotinoids, tracked across 15 individual compounds.
The finding, reported by the authors, is that people whose reported produce consumption produced a higher exposure score also tended to have higher levels of certain pesticide biomarkers measured in their urine. Some individual produce items, including strawberries, spinach, and bell peppers, showed up as more strongly linked to elevated urinary levels than others. That association held only after potatoes were removed from the analysis; with the full produce set as originally compiled, the relationship between exposure score and biomarker level did not hold. That qualification is not a footnote. It is part of the finding, and reporting the association without it overstates what the data actually showed. The correlation, where it exists, is between a dietary pattern and a laboratory measurement in the same people at the same point in time, not a fixed relationship across every produce item studied.
This study's authors work for the Environmental Working Group, whose own commercial content, its Dirty Dozen list, its Skin Deep and Food Scores databases, its press releases, is not something PurityIQ cites, because EWG's own terms restrict commercial use of that material. This is not that. The paper itself ran through independent peer review at a scientific journal and stands as a citable study regardless of who wrote it, the same as any other peer-reviewed research. The distinction matters enough to state plainly: this article cites the journal article, not EWG, and would cite the same paper if any other research group had authored it.
Cumulative or "dietary pattern" scoring like this is a departure from how pesticide residue findings are usually reported, which is one compound on one commodity at a time. USDA PDP data has existed since 1991 and is built for exactly that kind of single-residue reporting: does this apple have this fungicide, at what concentration, against what EPA tolerance. A cumulative score instead asks what a person's whole shopping basket adds up to, and biomonitoring data from NHANES is what lets a researcher check that math against a real biological measurement rather than a modeled estimate. That pairing, of PDP's residue-testing infrastructure with NHANES's biomonitoring infrastructure, is a newer analytic move than either program was originally built around, and researchers have been building similar exposure scores for other environmental variables for years. This study applies the technique to produce for the first time in a peer-reviewed venue at this scale.
What the study does not show matters as much as what it does. It is cross-sectional: everyone was measured once, at one point in time, so the paper cannot establish that eating a given food caused a given biomarker level, only that the two were associated in that sample. It says nothing about health outcomes. There is no disease endpoint, no illness rate, no comparison to any measure of harm anywhere in the paper. It is an exposure and biomarker study, not a health-effects study, and it should not be read as one. The authors themselves have acknowledged substantial uncertainty in translating a food residue measurement into an actual internal dose, and independent food-safety commentary on the paper has noted that some of the produce-to-biomarker relationships were modest, and inconsistent across different commodities, and that the study did not compare any measured biomarker level to a toxicological threshold of concern. Detecting a biomarker is not the same as establishing risk. The paper draws on one NHANES cycle and 1,837 people; it is a single biomonitoring snapshot, not a nationally exhaustive or longitudinal one.
For a shopper, this study is a data point about how dietary pattern and internal exposure move together, not a verdict on any individual fruit or vegetable. It does not tell you that a food is unsafe, and it does not tell you what level of exposure would be a health concern, because it wasn't designed to. What it does confirm is that the residue numbers USDA PDP publishes for a given commodity are not purely theoretical: for at least some pesticide classes and some produce items, higher expected exposure based on those residue numbers lined up with higher measured levels in people's urine. Whether that matters to any individual shopper is a separate question the study doesn't answer, and neither does this article.
This is the kind of record PurityIQ exists to surface without translating it into a score of its own. The app puts the underlying residue data, the regulatory tolerances, and studies like this one in front of a shopper at the point of decision, cited to where they came from, with no grade layered on top. You see what was measured and by whom. You decide what to do with it.