A robust sebum, oil, and particulate pollution model for assessing cleansing efficacy of human skin

With increasing concerns over the rise of atmospheric particulate pollution globally and its impact on systemic health and skin ageing, we have developed a pollution model to mimic particulate matter trapped in sebum and oils creating a robust (difficult to remove) surrogate for dirty, polluted skin.

To evaluate the cleansing efficacy/protective effect of a sonic brush vs. manual cleansing against particulate pollution (trapped in grease/oil typical of human sebum).

The pollution model (Sebollution; sebum pollution model; SPM) consists of atmospheric particulate matter/pollution combined with grease/oils typical of human sebum. Twenty subjects between the ages of 18-65 were enrolled in a single-centre, cleansing study comparisons between the sonic cleansing brush (normal speed) compared to manual cleansing. Equal amount of SPM was applied to the centre of each cheek (left and right). Method of cleansing (sonic vs. manual) was randomized to the side of the face (left or right) for each subject. Each side was cleansed for five-seconds using the sonic cleansing device with sensitive brush head or manually, using equal amounts of water and a gel cleanser. Photographs (VISIA-CR, Canfield Imaging, NJ, USA) were taken at baseline (before application of the SPM), after application of SPM (pre-cleansing), and following cleansing. Image analysis (ImageJ, NIH, Bethesda, MD, USA) was used to quantify colour intensity (amount of particulate pollutants on the skin) using a scale of 0 to 255 (0 = all black pixels; 255 = all white pixels). Differences between the baseline and post-cleansing values (pixels) are reported as the amount of SPM remaining following each method of cleansing.

Using a robust cleansing protocol to assess removal of pollutants (SPM; atmospheric particulate matter trapped in grease/oil), the sonic brush removed significantly more SPM than manual cleansing (P < 0.001). While extreme in colour, this pollution method easily allows assessment of efficacy through image analysis.