Background: To better compare the progression of dark circles and the aging process in Chinese skin. A total of 100 589 Chinese males and 1 838 997 Chinese females aged 18 to 85, without facial skin conditions, and who had access to a smartphone with a high-resolution camera all took selfies.
Method: Using a smartphone application with a built-in artificial intelligence algorithm, facial skin diagnostic evaluated the selfies and score the severity of the dark circles with four other facial indicators (including skin type, Pores, Acne vulgaris, and Blackheads). Basic information was collected with online questionnaire, including their age, gender, skin sensitivity, and dietary habits.
Results: In users between the age of 18 and 59, the prevalence of comprehensive, pigmented, and structural type of dark circles all rose with age. However, between the age of 60 and 85, the intensity of all types of dark circles diminished. Besides, vascular dark circles progressively worsen from the age of 18 to their peak at 39, and then gradually decline with age. Females typically have more pronounced black circles under their eyes than males in China. Bad eating habits, urbanization, regular cosmetics use, and sensitive skin positively correlate with severe dark circles. Vascular, comprehensive dark circles were worse in spring. Both pigmented and structural dark circles were worse in the summer. The results indicated that the intensity of dark circles was influenced by oily skin, wide pores, severe blackheads, and severe acne.
Conclusions: Chinese men and women differed noticeably in the prevalence of each face aging indicator and the appearance of aging dark circles. Selfies could be automatically graded and examined by artificial intelligence, which is a quick and private method for quantifying signs of facial aging and identifying major problems for different populations. Artificial intelligence would assist in the development of individualized preventive and therapeutic interventions.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10603312 | PMC |
http://dx.doi.org/10.1111/srt.13492 | DOI Listing |
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