Toxins (Jun 2025)

Evaluating Bias in Self-Reported Symptoms During a Cyanobacterial Algal Bloom

  • John S. Reif,
  • Rebecca Koszalinski,
  • Malcolm M. McFarland,
  • Michael L. Parsons,
  • Rachael Schinbeckler,
  • Judyta Kociolek,
  • Alex Rockenstyre,
  • Adam M. Schaefer

DOI
https://doi.org/10.3390/toxins17060287
Journal volume & issue
Vol. 17, no. 6
p. 287

Abstract

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Algal blooms produced by cyanobacteria liberate microcystins and other toxins that create a public health hazard. During the 2018 bloom of Microcystis aeruginosa in Florida, USA, residential and recreational exposures were associated with an increased risk of self-reporting respiratory, gastrointestinal, or ocular symptoms for 125 participants. Subsequently, 207 persons were interviewed between 2019 and 2024 in the absence of large-scale algal blooms and were considered non-exposed. Analyses of cyanotoxins and brevetoxins in water and air showed only intermittent, background levels of toxins during the non-bloom period. The purpose of this report was to compare symptom reporting between active bloom and non-bloom periods. The assessment of information bias from self-reported symptoms is an important issue in epidemiologic studies of harmful algal blooms. During the non-bloom period, no statistically significant associations with residential, recreational, or occupational exposures were found for any symptom group. Estimated risks for respiratory, gastrointestinal, and ocular symptoms, headache, and skin rash were significantly higher for persons sampled during the bloom than the non-bloom period with odds ratios (ORs) of 2.3 to 8.3. ORs for specific respiratory symptoms were also significantly elevated. After adjustment for confounders and multiple exposures in multivariable analyses, the differences in symptom reporting between bloom and non-bloom periods remained statistically significant. In summary, the use of self-reported symptoms in this epidemiologic study of exposure to a cyanobacterial algal bloom did not appear to introduce substantial information bias.

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