An artificial intelligence powered study of enlarged facial pore prevalence on one million Chinese from different age groups and its correlation with environmental factors

Background: Enlarged pores are amidst one of the top cosmetic concerns, especially among Chinese. Many small-group studies have been conducted in understanding their prevalence and beauty relevance. Nonetheless, population-level investigations are still lacking because of gaps in data collection and processing of large-scale studies. Owing to the recent technological advancement enabled by artificial intelligence, databases on the scale of millions can be processed and analyzed readily. Materials and methods: Powered by big data capabilities, revealed a number of novel trends on pore conditions among over-a-million Chinese participants recruited via the "You Look Great Today" mobile application. A scoring model was constructed, which demonstrated high consistency with conventional grading method from dermatologists. Environmental data (weather, air pollution, light at night satellite) were applied to correlate with pore severity. Results: Intraclass correlations between the two scoring systems were strong, with coefficients ranging from 0.79 to 0.92 for different facial areas. Statistical differences in pore severity among all four facial areas (cheek, forehead, nose, and overall) were observed, with the cheek exhibiting the most severe pore condition. Interestingly, Chinese men suffer from more severe pore condition than females. Multiple environmental factors exhibited strong correlations with cheek pore severity and were statistically fitted into linear regressions. Specifically, incremental risk with Each Low Temperature, Low Humidity, And High Solar Exposure correlate to worse cheek pore conditions. Although the Pearson correlation was low between cheek pore severity and light at night, comparison between representative cities demonstrated that in geologically similar cities, higher light at night corresponds to more severe cheek pore conditions. Conclusion: Our study is showcasing a robust and reliable AI model in facial pore evaluation. More importantly, insights uncovered using this facile approach also bear significant cosmetic ramifications in treatment of pore enlargement.