P.A.D.D.L.E.: a hypothesis generation tool for assessing pollution’s potential role in disease

TL;DR

This paper introduces P.A.D.D.L.E., a tool linking pollution exposure to disease patterns using healthcare data and environmental pollutants.

Contribution

P.A.D.D.L.E. is a novel interactive web tool connecting pollution data to disease diagnoses using statistical modeling.

Findings

Neurodevelopment and epithelial inflammation diseases were most linked to toxic exposures.

Associations were found between 61.9 million healthcare visits and 571 air pollutants across zip codes.

Demographic disparities in pollution exposure were identified using economic and healthcare access metrics.

Abstract

Since the 1960s, tens of thousands of chemicals have been added to the global market, yet the vast majority lack comprehensive health risk assessments. During this same period, industrialized nations have experienced dramatic increases in inflammatory diseases, raising concerns about environmental contributors. We aim to provide a tool for researchers to explore associations between environmental toxicant releases and diseases of interest, assess impacts of the route of exposure, connect findings to protein targets and biological pathways, map geographic “hot spots”, and identify at-risk populations. We employ multivariate, nonspatial elastic net regression and univariate, spatial mixed effects modeling to assess connections between 61.9 million health care visits for 5,984 diagnoses and 6-year averaged exposures to 571 air and 42 water pollutants across 16,451 zip codes. Economic confounders including regional deprivation indices and healthcare access metrics were included. Demographic disparities in environmental exposure burdens were also assessed. Our analysis revealed that diseases of neurodevelopment and epithelial inflammation were most frequently linked to mechanistically plausible toxic exposures. Ultimately, we created an interactive web tool, Pollution Associated Disease Diagnosis Likelihood Estimator (P.A.D.D.L.E.), that provides epidemiological associations to guide future research. We emphasize that these associations are based on observational data and require further validation studies to establish causal disease-toxicant relationships.

The online version contains supplementary material available at 10.1038/s41598-026-39836-2.

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