Statistical analyses of sunscreen usage survey data for the purpose of factor refinement influencing UV filter exposure in aquatic systems

Current environmental emissions assessments for UV filters in sunscreens used at the beach assume a uniform application rate. While this approach is both conservative and pragmatic, it fails to take into account consumer behaviors that could lead to a range of application values. This study explored diverse behavior, environmental, and other independent factors that may affect application rates by investigating results from an online survey with >2,000 participants. The survey included visual references that helped participants determine the mass of sunscreen lotion applied to their face and body. The resulting datasets for the face and body required curation to eliminate conflicting responses (e.g., “I don't typically apply sunscreen” and contradictory sunscreen application amount responses). Environmental variables tied to the zip codes of participants were investigated for their links with application rates. Generalized linear models (GLM) were used to assess the multivariate nature of participant attributes (e.g., income, skin tone), environmental factors (e.g., UV radiation by zip code) and others to self-report application rates. Akaike's Information Criterion was used to select highly significant models. An eight-variable model explained application thickness on the body, in order of statistical significance: amount of body submerged in water, time in water, gender identity, age, Fitzpatrick skin type, body reapplication, skin response to the sun, and time at the beach. The statistical analysis demonstrated that a clear, one-size-approach toward exposure assessment of UV filters in sunscreens at the beach may not be appropriate because several independent variables were significantly related to application rates to the face and body. The learnings from this study can be used to refine future online surveys. This can lead to realistic environmental emissions and exposure assessments that include diverse independent factors associated with sunscreen use at the beach as well as the ability to tailor emissions estimates to specific beach and aquatic environments thus providing the ability to better target environmental risk management actions.