Repurposing consumer sunscreen habits and practices survey data to guide the development of UV filter environmental exposure models and risk assessments.

OBJECTIVE: A key factor that is deficient in most environmental emissions assessments for UV filters is a keen understanding of consumer habits and practices that can inform realistic exposure assessments. This study utilized a large volunteer survey (>11 000 persons) that captured many factors that affect consumer-based loadings to aquatic environments. The purpose of this study was to utilize this large survey to identify factors that affect the amount of sunscreen products used by consumers. METHODS: Correlations among more than 20 variables were used to provide an understanding of the overall dataset and identify factors that may be related to the amount of sunscreen product applied to the body (i.e., application thickness). Forward multiple linear regressions were used to identify the relative importance of each of these factors alone and in combination with others in predicting the amount of applied sunscreen. RESULTS: The proportion of body surface area (BSA) covered by sunscreen was the primary factor related to application thickness, followed by body surface area of the survey participant, seasonal usage, Fitzpatrick skin type and the sun protection factor, respectively. Each of the five regression models examined was statistically highly significant. CONCLUSIONS: Comparisons to recommendations from the National Academies of Science, Engineering and Medicine parameters illustrated sufficient differences so as to encourage the development of future consumer habits and practice surveys that include factors beyond the scope of this study (e.g., activities, time of day, year, location, etc.) that can lead to improved exposure and risk assessments.

OBJECTIF: Un facteur clé qui est insuffisant dans la plupart des évaluations des émissions environnementales pour les filtres UV est une bonne compréhension des habitudes et pratiques des consommateurs qui peuve informer sur les évaluations réalistes de l'exposition. Cette étude a utilisé une vaste enquête auprès de volontaires (> 11 000 personnes) qui a pris en compte de nombreux facteurs affectant les habitudes des consommateurs dans des environnements aquatiques. L'objectif de cette étude était d'utiliser cette vaste enquête pour identifier les facteurs qui affectent la quantité de produit d'écran solaire utilisée par les consommateurs. MÉTHODES: Des corrélations entre plus de vingt variables ont été utilisées pour fournir une compréhension de l'ensemble des données et identifier les facteurs qui peuvent être liés à la quantité de produit d'écran solaire appliqué sur le corps (c.-à-d., épaisseur d'application). Des régressions linéaires multiples ont été utilisées pour identifier l'importance relative de chacun de ces facteurs seuls et en association avec d'autres pour prédire la quantité d'écran solaire appliqué. RÉSULTATS: La proportion de la surface corporelle (SC) couverte par l'écran solaire était le facteur principal lié à l'épaisseur de l'application, suivie de la surface corporelle du participant à l'enquête, de l'utilisation saisonnière, du type de peau (Fitzpatrick) et du facteur de protection solaire, respectivement. Chacun des cinq modèles de régression examinés était hautement significatif statistiquement. CONCLUSIONS: Les comparaisons avec les recommandations des Académies nationales de la science, de l'ingénierie et de la médecine ont mis en évidence des différences suffisantes pour encourager le développement de futures enquêtes sur les habitudes et les pratiques des consommateurs qui incluent des facteurs dépassant le champ d'application de cette étude (ex., activités, moment de la journée, année, lieu, etc.) qui peuvent conduire à une amélioration de l'exposition et des évaluations des risques.

A novel online survey approach designed to measure consumer sunscreen application thickness-implications for estimating environmental emissions.

BACKGROUND: The effects of ultraviolet (UV) filters in the aquatic environment have been well studied, but environmental exposures remain unclear and understudied. Consumer usage directly influences the amount of sunscreen products, and subsequently UV filters, potentially released into the environment. OBJECTIVE: To conduct a literature review of previous research into sunscreen application thickness, develop a questionnaire protocol designed to semi-quantify sunscreen usage by US consumers, and conduct a large-scale survey to determine a sunscreen application thickness (to face and body) that is more refined than conservative defaults. The United States Food & Drug Administration (US FDA) recommends a sunscreen application rate of 2 mg/cm2. This value is typically used as a worst-case assumption in environmental exposure assessments of UV filters. METHODS: Designed a novel approach to estimate lotion sunscreen application thickness using an online questionnaire protocol employing visual references and self-reported height and weight of the respondents. A literature review was also conducted to collect historical sunscreen usage. RESULTS: Over 9000 people were surveyed in the US, and after the dataset was refined, their sunscreen application thickness was estimated based on calculated body surface area and reported sunscreen amounts. The mean and median values for survey respondents are 3.00 and 1.78 mg/cm2, respectively, for facial application thickness and 1.52 and 1.35 mg/cm2, respectively, for body application thickness. Earlier research from 1985-2020 reported 36 of the 38 values are below the US FDA's recommended application thickness of 2 mg/cm2 (range 0.2-5 mg/cm2). IMPACT STATEMENT: This web-based survey is the first of its kind, designed specifically to quantify sunscreen application in a large and diverse set of consumers. This method provides a greater reach to larger populations thus enabling more granular data analysis and understanding. Exposure assessments of sunscreen ingredients typically use conservative parameters. These data can refine those assessments and allow for more informed and science-based risk management decisions.