Influence of cosmetic foundation cream on skin condition during treadmill exercise.

BACKGROUND: There is a growing trend of individuals wearing cosmetics while participating in physical activities. Nonetheless, there remains a need for further understanding regarding the effects of makeup on the facial epidermis during exercise, given the existing knowledge gaps. PURPOSE: This study aimed to evaluate the effects of a cosmetic foundation cream on skin conditions during physical activity. METHODS: Forty-three healthy college students, 20 males (26.3 ± 1.5 years) and 23 females (23.1 ± 1.0 years), were enrolled in this study. Foundation cream was applied to participants on half of the face in two different areas (MT: makeup T zone and MU: makeup U zone). The other half of the face served as internal control (T: non-makeup T zone and U: non-makeup U zones). Skin levels of moisture, elasticity, pore, sebum, and oil were measured using a skin analysis device (Aramhuvis, Gyeonggi, Republic of Korea) before and after a 20-min treadmill exercise. Paired t-test and independent t-test were performed for skin condition measurements at pre- and postexercise. RESULTS: The skin moisture levels in both the T and MT significantly increased after exercise (p < 0.05) (pre-T: 24.5 ± 1.3, post-T: 38.5 ± 3.5 and pre-MT: 18.7 ± 0.7, post-MT: 40.4 ± 4.8). Elasticity also significantly improved in both the T and MT (p < 0.05) (pre-T: 25.6 ± 1.3, post-T: 41.5 ± 3.5 and pre-MT: 20.0 ± 0.9, post-MT: 41.7 ± 3.7). The size of the pores in the T zone observed a significant increase after exercise (p < 0.05) (pre-T: 41.7 ± 2.1, post-T: 47.8 ± 2.4). The sebum levels in the T zone exhibited a reduction following physical activity, whereas there was a notable increase in sebum levels in the makeup zones (p < 0.05) (pre-MT: 2.4 ± 0.7, post-MT:4.2 ± 0.8 and pre MU 1.8 ± 0.34, post MU 4.9 ± 0.9). The oil level was increased in the non-makeup zones (pre-T: 6.1 ± 1.4, post-T: 11.8 ± 2.0 and pre-U: 7.3 ± 1.5, post-U: 11.9 ± 1.9; p < 0.05) and decreased in the makeup zones (pre-MT: 13.3 ± 1.9, post-MT: 7.4 ± 2.3 and pre-MU: 22.1 ± 2.4, post-MU: 3.2 ± 1.0; p < 0.05). CONCLUSIONS: The findings suggest that using foundation cream during aerobic exercise can reduce skin oil, causing dryness. Additionally, makeup can clog pores and increase sebum production. Therefore, wearing makeup may not be recommended for people with dry skin conditions based on the results of the current study. This research offers important insights to the public, encouraging them to consider the possible consequences of using makeup while exercising.

Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants.

Background: Scalp-related symptoms such as dandruff and itching are common with diverse underlying etiologies. We previously proposed a novel classification and scoring system for scalp conditions, called the scalp photographic index (SPI); it grades five scalp features using trichoscopic images with good reliability. However, it requires trained evaluators.Aim: To develop artificial intelligence (AI) algorithms for assessment of scalp conditions and to assess the feasibility of AI-based recommendations on personalized scalp cosmetics.Methods: Using EfficientNet, convolutional neural network (CNN) models (SPI-AI) ofeach scalp feature were established. 101,027 magnified scalp images graded according to the SPI scoring were used for training, validation, and testing the model Adults with scalp discomfort were prescribed shampoos and scalp serums personalized according to their SPI-AI-defined scalp types. Using the SPI, the scalp conditions were evaluated at baseline and at weeks 4, 8, and 12 of treatment.Results: The accuracies of the SPI-AI for dryness, oiliness, erythema, folliculitis, and dandruff were 91.3%, 90.5%, 89.6%, 87.3%, and 95.2%, respectively. Overall, 100 individuals completed the 4-week study; 43 of these participated in an extension study until week 12. The total SPI score decreased from 32.70 ± 7.40 at baseline to 15.97 ± 4.68 at week 4 (p < 0.001). The efficacy was maintained throughout 12 weeks.Conclusions: SPI-AI accurately assessed the scalp condition. AI-based prescription of tailored scalp cosmetics could significantly improve scalp health.