Skip to main content
NCBI home page
Skin Research and Technology logoLink to Skin Research and Technology
. 2025 May 19;31(2-5):e70172. doi: 10.1111/srt.70172

A Study on the Difference in Aging Characteristics of Sensitive and Non‐Sensitive Skin

Lin Guihua 1, Jiang Wencai 2, Du Shan 1, Jiang Yanzhu 1, Doohyun Baek 1, YunHa Lee 1,✉, Tan Yimei 2,✉
PMCID: PMC12086371

ABSTRACT

Background

According to Euromonitor and T Mall data statistics from 2017 to 2022, the Chinese market for sensitive skin (SS) skincare is growing by 20% every year, and anti‐aging concept cosmetics for sensitive skin are becoming popular. There are few studies on the difference in aging between sensitive and non‐sensitive skin.

Objectives

This study is to determine whether sensitive skin ages faster than non‐sensitive skin.

Method

Eighty subjects aged 25–50 years each from sensitive and non‐sensitive skin participated in this clinical trial. trans‐epidermal water loss (TEWL), CIE‐L* a*b* values, gloss, hydration, sebum content, dermis density, elasticity, wrinkles, smoothness, artificial intelligence (AI)‐estimated skin age, and pores were evaluated in subjects with sensitive and non‐sensitive skin.

Results

In the 25‐ to 29‐year‐old group, the pore score and nasolabial fold count of non‐sensitive skin were significantly lower than those of sensitive skin (p < 0.05), but the transparency was significantly higher than that of sensitive skin (p < 0.05). There was a significant difference between groups in the MAE value between AI skin age and chronological age, and the AI‐estimated skin age of sensitive skin is significantly older than that of non‐sensitive skin (p < 0.05). There were no significant differences between sensitive and non‐sensitive skin in other parameters (p > 0.05). In the 30‐ to 34‐year‐old group, the TEWL value and a* value of non‐sensitive skin are significantly lower than those of sensitive skin, but the L* value and glossiness are significantly higher than those of sensitive skin (p < 0.05). There is no statistical difference in other parameters between sensitive and non‐sensitive skin (p > 0.05). In the 35‐ to 50‐year‐old group, sensitive skin demonstrated better performance only in crow's feet compared to non‐sensitive skin, with no significant differences observed in other parameters between the groups. (p > 0.05).

Conclusion

The phenomenon of premature aging in sensitive skin is more obvious, but as age increases, the difference in aging is not obvious. Early anti‐aging care for sensitive skin is necessary.

Keywords: aging, AI‐estimated skin age, non‐sensitive skin, sensitive skin, skin color, wrinkles

1. Introduction

Sensitive skin (SS) was defined as the occurrence of unpleasant sensations (stinging, burning, pain, pruritus, and tingling sensations) in response to stimuli that normally should not provoke such sensations [1]. The prevalence of SS is 49.6% in Chinese women. Shanghai has the highest percentage of sensitive skin among seven cities: Shanghai, Beijing, Guangdong, Henan, Sichuan, Chongqing, and Shandong [2]. A self‐assessed questionnaire is associated with sensitive skin featuring an oily and red face without impaired barrier function, whereas a lactic acid sting test (LAST) is suitable to identify fragile skin barriers and enhance blood flow on the face. A combination of both methods to diagnose sensitive skin might be more reliable [3].

TRPV1 expression is upregulated in subjects with sensitive skin (LAST [+]) and correlates with the intensity of the symptoms [4]. The direct consequence of the TRPV1 activation is the inflow of extracellular Ca2+ into the cells, increasing in Ca2+ concentration, which mediates the basic activities of various cells, such as cell proliferation and apoptosis [5].

As part of a cross‐sectional study, skin topographic features, skin color/color heterogeneities, skin chromophores, and biophysical properties were collected from 116 Caucasian and Chinese female volunteers aged 30–65 years in Ireland and China. The results revealed that the wrinkles/texture and ptosis/sagging are predominant factors across almost all ethnicities [6]. Among Chinese male subjects, a statistically significant correlation was demonstrated between chronological age and convolutional neural network (CNN)‐predicted age based on morphological analysis of the nasolabial folds, along with forehead wrinkles, infrapalpebral grooves, and glabellar lines [7]. In Japanese women, age significantly correlated with worsening periorbital/crow's feet/glabellar wrinkles, deepened nasolabial folds, lip texture changes, and cheek pigmentation [8]. In another study involving 129 healthy East Asian women, skin elasticity was measured at the cheek and lower eyelid areas on both sides of the face. The results showed significant negative correlations between age and the R2 and R7 parameters, which represent skin elasticity after deformation [9]. The CIE L*a*b* color space, known for its ability to approximate human vision physiology, has proven particularly suitable for skin color measurement. Using the CIE L*a*b* color space, researchers observed statistically significant skin darkening with age across all ethnic groups (African American, Caucasian, Chinese, and Mexican). Additionally, Chinese subjects exhibited evidence of skin yellowing with age [10]. These results underscore the role of pigmentation changes in the aging process.

Current research on skin aging is extensive; however, studies focusing on the aging characteristics of individuals with sensitive skin and the differences in aging between sensitive and non‐sensitive skin populations are very limited. In this study, aging parameters were compared between the two groups to investigate the differences in aging characteristics between sensitive and non‐sensitive skin.

2. Methods

2.1. Study Subjects and Environment

This study enrolled 80 sensitive skin subjects and 80 non‐sensitive skin subjects aged 25–50. The recruitment criteria for individuals with sensitive skin required a positive result in the 10% LAST+, confirming skin sensitivity, along with a self‐reported history of sensitive skin lasting more than 5 years. For non‐sensitive skin subjects, the criteria included a negative result in the 10% LAST− and self‐identification as non‐sensitive (Figure 1). Subjects with skin diseases at the test site that may affect the evaluation of the trial results, as well as those with a highly allergic constitution, were excluded. There is no significant difference in age between sensitive and non‐sensitive skin subjects recruited from 25 to 50 years of age (p > 0.05). All subjects should be in the habit of applying sunscreen and should be exposed to UV for no more than 2 h per day. Informed consent was obtained for all subjects before the study. The study was performed according to good clinical practices and the principles of the Declaration of Helsinki. This study was approved by the ethical committee of Shanghai Skin Disease Hospital (approval number: 2023–38).

FIGURE 1.

FIGURE 1

Open in a new tab

Age distribution of subjects. A total of 20 subjects with sensitive skin and 20 with non‐sensitive skin were recruited for both the 25–29 and 30–34 age groups, while 40 subjects per skin type were enrolled for the 35–50 age group.

Before skin measurements were taken, subjects cleaned their faces and waited 30 min at a controlled temperature of 20 ± 2°C and a relative humidity of 50 ± 10%.

2.2. Measurement

2.2.1. LAST

Lactic acid (purity >98%, Sigma, USA) was diluted with distilled water to make a concentration of 10%. Drop 50 µL of 10% lactic acid and distilled water, respectively, onto a filter paper with a diameter of 8 mm, and randomly place them on the nasolabial folds on both sides of the subject. The subjects evaluated the degree of discomfort, such as itching, tingling, and burns, at 30 s, 2.5, and 5 min, respectively. If the sum of the scores was ≥3 on the side of the lactic acid application, the subject was defined as a positive (LAST +); otherwise, as a negative (LAST −) [11].

2.2.2. Measurement of Skin Hydration

The skin hydration was measured at the cheek using a Corneometer (Courage + Khazaka, Köln, Germany). The results were expressed in arbitrary units (a.u.).

2.2.3. Measurement of Trans‐Epidermal Water Loss (TEWL)

Skin TEWL was measured at the cheek using a Tewameter (Courage + Khazaka, Köln, Germany). The results were expressed digitally in g/(m2·h).

2.2.4. Measurement of Sebum Content

Sebum content was determined using a Sebumeter (Courage + Khazaka, Köln, Germany). The results were expressed in µg/cm2.

2.2.5. Measurement of Skin Color, Gloss, and Transparency

Facial images were captured using a VISIA‐CR (Canfield, Fairfield, USA). Photographs taken under Visia‐CR cross‐polarized light were analyzed to determine the L* (lightness), a* (redness), and b* (yellowness) values. Cross‐polarized light enables more objective characterization of skin color and has been utilized to assess color changes in various conditions [12, 13]. ITA° is a metric used to quantify skin tone based on lightness (L*) and yellowness (b*), calculated using the following equation: ITA°  = {arctan[(L*−50)/b*]} * 180/π [14]. The images captured using the dual‐polarized imaging system were utilized for analyzing transparency [15], while parallel‐polarized light was used to evaluate gloss [16]. The images were analyzed using Image Pro‐Plus 7.0 software.

2.2.6. Measurement of Skin Density

Dermascan C, high‐frequency (20 MHz) ultrasound enables non‐invasive evaluation of the density of the dermis (Dermascan, Cortex Technology, Denmark). The measurement area is the cheek.

2.2.7. Measurement of Skin Elasticity

Skin elasticity was determined using a Cutometer (Courage + Khazaka, Köln, Germany). Skin elasticity (R2) measurement was performed on the cheek. The R2 parameter represents the overall elasticity, indicating the rate at which the skin, after being maximally stretched by the pressure zone, recovers to its original state.

2.2.8. Measurement of Skin Wrinkles

The Primos‐CR (Canfield, USA) system utilizes digital stripe projection technology for optical 3D measurement. A parallel stripe patten is projected onto the skin and captured by a digital camera's CCD chip. The system consists of a freely movable optical measurement head connected to an evaluation computer. The measurement head is mounted on a dedicated positioning device that stabilizes the subject's face and allows precise alignment with the target area (e.g., the eye corner). Skin surface microtopography induces deflections in the projected stripes, enabling 3D reconstruction based on elevation differences. These deflections provide both qualitative and quantitative data on skin profile, which are digitized and analyzed using the system's proprietary software [17]. ROIs (regions of interest) were delineated in the lateral periocular region (for crow's feet assessment) and along the nose to the corners of the mouth (for nasolabial fold evaluation). The data that are generated represents the measurement value of the detected features within the masked ROI.

2.2.9. Measurement of Skin Smoothness

Skin smoothness (SEsm) was assessed on the cheek using a Visioscan VC20 (C+K, Köln, Germany). Through this unique high‐resolution UV light, the camera system directly captures the active skin surface; it then analyzes the skin surface shape state, skin roughness, and drying process. The software can analyze the skin's various parameters of the surface.

2.2.10. Artificial Intelligence (AI)‐Estimated Skin Age (Dr. AMORE v1.2, AMOREPACIFIC)

AI‐estimated skin age was analyzed using an AI facial aging diagnostic system. It is a deep learning‐based system for diagnosing facial skin aging through image analysis, which provides intuitive and quantifiable age levels for overall facial skin aging [18].

2.2.11. Visual Assessment of Skin Pores

The subjects were visually assessed by an evaluator under a light source with an illumination intensity of 5500–6500 lx, using the following pore evaluation scale (Figure 2). The pore scoring scale ranged from 1 to 9, where 1 indicated small pores and 9 represented large, visibly prominent pores. The pore images were collected from Chinese female subjects for standardized grading references.

FIGURE 2.

FIGURE 2

Open in a new tab

Criteria of visual assessment for pore. Nine reference images demonstrate the pore severity gradient, where: Visual score 1: Small pores, Visual score 9: Large, visibly prominent pores.

2.2.12. Visual scoreVisual scoreStatistical Analysis

Statistical analyses were performed using the IBM SPSS Statistics for Windows Version 25.0 (IBM Cor.). The difference between groups was evaluated using t‐test for parametric data and Wilcoxon's test for nonparametric ones. p value < 0.05 was considered significant.

3. Results

3.1. Difference Between Sensitive and Normal Skin in the Age Group of 25–29

The pore score and nasolabial fold count of non‐sensitive skin were significantly lower than those of sensitive skin (p < 0.05), but the transparency was significantly higher than that of sensitive skin (p < 0.05). There was a significant difference in the MAE values between AI‐estimated skin age and chronological age across groups, and the AI‐estimated skin age of sensitive skin is significantly older than that of non‐sensitive skin (p < 0.05). There were no significant differences between sensitive skin and non‐sensitive skin in other parameters (p > 0.05). The results are illustrated in Figure 3.

FIGURE 3.

Skin parameters, such as the Sebum (A), Hydration (B), Trans‐epidermal water loss (TEWL) (C), L* value (D), a* value (E), b* value (F), Individual typology angle (ITA°) (G), Smoothness (H), Dermis density (I), Gloss (J), Skin elasticity (R2)‐ (K), Nasolabial fold depth (L), Nasolabial fold count (M), Crow's feet depth (N), Crow's feet count (O), Transparency (P), Artificial intelligence (AI)—estimated skin age (Q), and Pore score (R), of sensitive skin and non‐sensitive skin. *p < 0.05.

graphic file with name SRT-31-e70172-g005.jpg

graphic file with name SRT-31-e70172-g008.jpg

Open in a new tab

3.2. Difference between sensitive and normal skin in the age group of 30–34

The TEWL value, a* value, and Nasolabial fold depth of non‐sensitive skin are significantly lower than those of sensitive skin, but the L* value, ITA° and gloss are significantly higher than those of sensitive skin (p < 0.05). There is no statistical difference in other parameters between sensitive skin and non‐sensitive skin (p > 0.05). The results are illustrated in Figure 4.

FIGURE 4.

Skin parameters, such as the Sebum (A), Hydration (B), Trans‐epidermal water loss (TEWL) (C), L* value (D), a* value (E), b* value (F), Individual typology angle (ITA°) (G), Smoothness (H), Dermis density (I), Gloss (J), Skin elasticity (R2) (K), Nasolabial fold depth (L), Nasolabial fold count (M), Crow's feet depth (N), Crow's feet count (O), Transparency (P), Artificial intelligence (AI)—estimated skin age (Q), and Pore score (R), of sensitive skin and non‐sensitive skin. *p < 0.05.

graphic file with name SRT-31-e70172-g006.jpg

graphic file with name SRT-31-e70172-g007.jpg

Open in a new tab

3.3. Difference between sensitive and normal skin in the age group of 35–50

The Crow's feet depth of non‐sensitive skin is significantly higher than that in sensitive skin (p < 0.05). There were no statistical differences in other parameters between sensitive skin and non‐sensitive skin (p > 0.05). The results are illustrated in Figure 5.

FIGURE 5.

Skin parameters, such as the Sebum (A), Hydration (B), Trans‐epidermal water loss (TEWL) (C), L* value (D), a* value (E), b* value (F), Individual typology angle (ITA°) (G), Smoothness (H), Dermis density (I), Gloss (J), Skin elasticity (R2) (K), Nasolabial fold depth (L), Nasolabial fold count (M), Crow's feet depth (N), Crow's feet count (O), Transparency (P), Artificial intelligence (AI)—estimated skin age (Q), and Pore score (R), of sensitive skin and non‐sensitive skin. *p < 0.05.

graphic file with name SRT-31-e70172-g004.jpg

graphic file with name SRT-31-e70172-g002.jpg

Open in a new tab

4. Discussion

With the expansion of the sensitive skin‐specific cosmetics market in China, the concept that sensitive skin is more prone to aging is gradually gaining attention. However, research on the aging of sensitive skin remains limited. This study investigated the differences in skin aging between sensitive and non‐sensitive skin across different age groups. The results revealed significant variations in skin aging parameters, with sensitive skin exhibiting more pronounced signs of aging in the 25–29 and 30–34 age groups. In contrast, no significant differences were observed between sensitive and non‐sensitive skin in the 35–50 age group.

In the 25–29 age group, the skin condition of sensitive skin was worse than of non‐sensitive skin in terms of nasolabial folds, transparency, and pore score. Transparency was showed a steady decline with age [19]. A study reveals distinct gender‐specific aging patterns in Chinese subjects: for women, marionette lines emerge as primary aging markers, with age perception predominantly driven by upper facial features (forehead and crow's feet wrinkles). In contract, Chinese men exhibit milder marionette line development and demonstrate more pronounced lower facial aging (nasolabial folds and facial ptosis), particularly before age 40. Interestingly, while clinical measurements show men develop more severe upper facial signs, their perceived aging remains more associated with lower facial changes‐presenting an inverse relationship between anatomical aging and perceptual aging cues across genders [20]. Enlarged pores are not merely a textural concern but serve as early morphological markers of aging‐progressive pore elongation, expansion, and coalescence directly contribute to pre‐wrinkle formation and ultimately exacerbate wrinkle severity [21, 22, 23, 24]. Research indicates that the highest prediction accuracy (lowest MAE) is achieved for hands in the 30–40 age group and for facial images in the 20–45 age range [25]. In our study, AI‐estimated skin age was higher in the 25–29 sensitive skin group compared to non‐sensitive skin, which may represent early signs of aging.

In the 30–34 age group, the skin condition of sensitive skin was worse than that of non‐sensitive skin in terms of nasolabial folds, TEWL, ITA°, L* value, a* value, and gloss. A study revealed a consistent age‐related decline in Shanghainese women's skin lightness (L*), with an average decrease of approximately 1.0 unit per decade [26]. Research demonstrates that the Chinese population exhibits a comparable statistically significant decline in ITA° at a rate of approximately 1 unit per 4‐year period, while a* values show a progressive increase with advancing age [27]. On the cheeks, darkening is statistically significant for the Chinese group (age range 20–50 < 40–60 < 50–80) [28]. A study revealed that while “tired appearance” and “healthy glow” facial characteristics showed a negative correlation, statistical analyses demonstrated that tired appearance features had a significantly stronger association with perceived age [29].

The observed differences in aging characteristics between sensitive and non‐sensitive skin in the 25–29 and 30–34 age groups may be associated with stress factors. According to the WHO‐5 well‐being index, 44% of Asian women aged 18–34 experience poor mental well‐being. Older adults tend to report lower subjective stress levels and less negative stress appraisal during the anticipation phase compared to younger adults. Notably, 76.5% of dermatologists agreed that there is a strong connection between stress and skin aging [30, 31]. Psychological stress impacts skin health by disrupting immune and neuroendocrine function. This exacerbates skin diseases (e.g., psoriasis, atopic dermatitis [AD]) while the visible stigma of these conditions further worsens psychological distress, creating a vicious cycle [32]. It may also be associated with poor sleep habits among young individuals. Skin hydration and elasticity were decreased with sleep restriction. Skin recovery time was slower in the 4‐h sleep period than in the 8‐h sleep period. Elasticity was most affected by reduced sleep [33]. This study did not investigate subjects’ sleep patterns, which warrants further research in future studies.

For the 30–34 age group, the TEWL of sensitive skin was significantly higher than that of non‐sensitive skin. The poorer skin aging indicators in the 30–34 age group with sensitive skin may be related to barrier dysfunction. TEWL is a key indicator of skin barrier function. Skin barrier serves as the natural frontier between the inner organism and the environment, protecting against various external factors such as chemical, environmental, and physical stress, including UV radiation [34]. Sensitive skin is less resistant to external stimuli compared to healthy skin. A wide range of environmental factors, such as solar ultraviolet light and environmental pollution, can increase the production of reactive oxygen species (ROS) in the skin [35, 36]. Prolonged exposure to high levels of ROS can cause DNA strand breaks and point mutations, and the accumulation of such oxidative DNA damages can lead to genomic instability [37]. Furthermore, epidermal permeability barrier dysfunction likely contributes to inflammaging, as epidermal dysfunction predisposes individuals to inflammatory skin conditions such as contact dermatitis, AD, and psoriasis, which may further play a role in the pathogenesis of aging‐related disorders [38].

In the 35–50 age group, sensitive skin demonstrated better performance only in crow's feet compared to non‐sensitive skin, with no significant differences observed in other parameters between the groups. The minimal differences between sensitive and non‐sensitive skin may be related to the decline in the prevalence of very sensitive skin with increasing age. According to research, the total prevalence of very sensitive and sensitive skin was 16.44% in the younger group (<25 years), 14.14% in the middle group (25–49 years), and 9.63% in the older group (≥50 years). The prevalence of sensitive skin gradually decreases with increasing age [39]. Additionally, the better condition of crow's feet in sensitive skin may be related to the fact that individuals with sensitive skin pay more attention to skincare. Further research is needed to explore this in the future.

5. Conclusion

This study aimed to investigate the differences in skin aging between sensitive and non‐sensitive skin by categorizing participants into different age groups for a detailed analysis. We found that no significant difference was observed for most of the tested aging attributes; however, some early signs of aging were detected in sensitive skin. In contrast, there were almost no differences observed in the older age groups. The significance of this study lies in providing reference results for the currently limited research on aging in sensitive skin. The findings suggest that individuals with sensitive skin need to pay attention to anti‐aging care, particularly starting from a younger age, to maintain skin health.

Conflicts of Interest

The authors declare no conflicts of interest.

Lin Guihua and Jiang Wencai are co‐first authors.

Contributor Information

YunHa Lee, Email: smile265@amorepacific.com.

Tan Yimei, Email: tanym@shskin.com.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  • 1. Misery L., Stander S., Szepietowski J. C., et al., “Definition of Sensitive Skin: An Expert Position Paper From the Special Interest Group on Sensitive Skin of the International Forum for the Study of Itch,” Acta Dermato‐Venereologica 97, no. 1 (2017): 4–6. [DOI] [PubMed] [Google Scholar]
  • 2. Xiao X., Qiao L., Ye R., et al., “Nationwide Survey and Identification of Potential Stress Factor in Sensitive Skin of Chinese Women,” Clinical, Cosmetic and Investigational Dermatology 13 (2020): 867–874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Pan Y., Ma X., Song Y. Q., et al., “Questionnaire and Lactic Acid Sting Test Play Different Role on the Assessment of Sensitive Skin: A Cross‐Sectional Study,” Clinical, Cosmetic and Investigational Dermatology 14 (2021): 1215–1225. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Ehnis‐Perez A., Torres‐Alvarez B., Cortes‐Garcia D., et al., “Relationship Between Transient Receptor Potential Vanilloid‐1 Expression and the Intensity of Sensitive Skin Symptoms,” Journal of Cosmetic Dermatology 15, no. 3 (2016): 231–237. [DOI] [PubMed] [Google Scholar]
  • 5. Sappington R. M., Sidorova T., Long D. J., et al., “TRPV1: Contribution to Retinal Ganglion Cell Apoptosis and Increased Intracellular Ca2+ With Exposure to Hydrostatic Pressure,” Investigative Ophthalmology & Visual Science 50, no. 2 (2009): 717. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Messaraa C., Doyle L., Mansfield A., et al., “Ageing Profiles of Caucasian and Chinese Cohorts—Focus on Hands Skin,” International Journal of Cosmetic Science (2019): 1–10. [DOI] [PubMed] [Google Scholar]
  • 7. Zhang Y., Jiang R., Kezele I., et al., “A New Procedure, Free From Human Assessment, That Automatically Grades Some Facial Skin Signs in Men From Selfie Pictures. Application to Changes Induced by a Severe Aerial Chronic Urban Pollution,” International Journal of Cosmetic Science 42, no. 2 (2020): 185–197. [DOI] [PubMed] [Google Scholar]
  • 8. Flament F, Velleman D, Yamashita E, et al., “Japanese Experiment of a Complete and Objective Automatic Grading System of facial Signs From Selfie Pictures: Validation With Dermatologists and Characterization of Changes Due to Age and Sun Exposures,” Skin Research and Technology 27, no. 4 (2021): 544–553. [DOI] [PubMed] [Google Scholar]
  • 9. Kim SH, Lee SJ, Kim HJ, et al., “Aging‐Related Changes in the Mid‐Face Skin Elasticity in East Asian Women,” Archives of Craniofacial Surgery 20, no. 3 (2019): 158–163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Rigal J. D., Mazis I. D., Diridollou S., et al., “The Effect of Age on Skin Color and Color Heterogeneity in Four Ethnic Groups,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 16 (2010): 168–178. [DOI] [PubMed] [Google Scholar]
  • 11. Jiang W. C., Wang J., Zhang H., et al., “Seasonal Changes in the Physiological Features of Healthy and Sensitive Skin,” Journal of Cosmetic Dermatology 21, no. 6 (2022): 2581–2589. [DOI] [PubMed] [Google Scholar]
  • 12. Hanlon K. L., “Cross‐Polarised and Parallel‐Polarised Light: Viewing and Photography for Examination and Documentation of Biological Materials in Medicine and Forensics,” Journal of Visual Communication in Medicine. 41 (2018): 3–8. [DOI] [PubMed] [Google Scholar]
  • 13. O'Sullivan R., Tom L. M., Bunya V. Y., et al., “Use of Crossed Polarizers to Enhance Images of the Eyelids,” Cornea 36 (2017): 631–635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Hong H. R., YI K., and Liu S., “A Mobile Application for Personal Colour Analysis,” Cogent Business & Management 6, no. 1 (2019): 1576828. [Google Scholar]
  • 15. Matsubara A. Cross‐Polarized and Parallel‐Polarized Light Were Utilized to Assess Skin Transparency. IFSCC Congress 2006.
  • 16. Bae E. J., Seo S. H., Hye Y. C., et al., “A Quantitative Assessment of the human Skin Surface Using Polarized Light Digital Photography and Its Dermatologic Significance,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 16, no. 3 (2010): 270–274. [DOI] [PubMed] [Google Scholar]
  • 17. Fujimura T., Haketa K., Hotta M., et al., “Global and Systematic Demonstration for the Practical Usage of a Direct in Vivo Measurement System to Evaluate Wrinkles,” International Journal of Cosmetic Science 29 (2007): 423–436. [DOI] [PubMed] [Google Scholar]
  • 18. Park S. R., Park H. G., Lee S. R., et al., “Facial Age Evaluated by Artificial Intelligence System, Dr. AMORE®: An Objective, Intuitive, and Reliable New Skin Diagnosis Technology,” Journal of Cosmetic Dermatology 23, no. 4 (2024): 1510–1512. [DOI] [PubMed] [Google Scholar]
  • 19. Hastie I. R. and Millard P. H., “The Quantification of Skin Transparency,” British Journal of Dermatology 108, no. 3 (1983): 315–320. [DOI] [PubMed] [Google Scholar]
  • 20. Flament F., Abric A., and Amar D., “Gender‐Related Differences in Facial Aging of Chinese Subjects and Their Relations With Perceived Ages,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 26, no. 6 (2020): 905–913. [DOI] [PubMed] [Google Scholar]
  • 21. Jang S. I., Kim E. J., and Lee H. K., “A Method of Evaluating Facial Pores Using Optical 2D Images and Analysis of Age‐Dependent Changes in Facial Pores in Koreans,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 24 (2018): 304–308. [DOI] [PubMed] [Google Scholar]
  • 22. Jung H. J., Ahn J. Y., Lee J. I., et al., “Analysis of the Number of Enlarged Pores According to Site, Age, and Sex,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 24 (2018): 367–370. [DOI] [PubMed] [Google Scholar]
  • 23. Dissanayake B., Miyamoto K., Purwar A., et al., “New Image Analysis Tool for Facial Pore Characterization and Assessment,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 25 (2019): 631–638. [DOI] [PubMed] [Google Scholar]
  • 24. Lee S., Cherel M., Gougeon S., et al., “Identifying Patterns Behind the Changes in Skin Pores Using 3‐Dimensional Measurements and K‐Means Clustering,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 28 (2022): 3–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Georgievskaya A., Tlyachev T., Kiselev K., et al., “Predicting human Chronological Age via AI Analysis of Dorsal Hand Versus Facial Images: A Study in a Cohort of Indian Females,” Experimental Dermatology 33, no. 3 (2024): e15045. [DOI] [PubMed] [Google Scholar]
  • 26. Qiu H. X., Flament F., Long X. H., et al., “Seasonal Skin Darkening in Chinese Women: The Shanghaiese Experience of Daily Sun Protection,” Clinical, Cosmetic and Investigational Dermatology 15 (2022): 2101–2115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Qiu H. X., Li X. H., Ye C. D., et al., “Instrumental and Clinical Studies of the Facial Skin Tone and Pigmentation of Shanghaiese Women. Changes Induced by Age and a Cosmetic Whitening Product,” International Journal of Cosmetic Science 34, no. 1 (2012): 49–54. [DOI] [PubMed] [Google Scholar]
  • 28. Rigal J. D., Mazis I. D., Diridollou S., et al., “The Effect of Age on Skin Color and Color Heterogeneity in Four Ethnic Groups,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 16, no. 2 (2010): 168–178. [DOI] [PubMed] [Google Scholar]
  • 29. Flament F., Abric A., Amar D., et al., “Changes in Facial Signs Due to Age and Their Respective Weights on the Perception of Age, on a Tired‐look or a Healthy Glow Among Differently Aged Chinese Men,” International Journal of Cosmetic Science 42, no. 5 (2020): 452–461. [DOI] [PubMed] [Google Scholar]
  • 30. Anwar S. S., Ma L., Apolinar M. A., et al., “Understanding Mental Stress and Skin Aging Connection Among Dermatologists and Psychologists Through Real World Evidence,” Journal of the American Academy of Dermatology 87, no. 3 (2022): AB216. [Google Scholar]
  • 31. Mikneviciute G., Pulopulos M. M., Allaert J., et al., “Adult Age Differences in the Psychophysiological Response to Acute Stress,” Psychoneuroendocrinology 153 (2023): 106111. [DOI] [PubMed] [Google Scholar]
  • 32. Zhang H. Y., Wang M., Zhao X., et al., “Role of Stress in Skin Diseases: A Neuroendocrine‐immune Interation View,” Brain, Behavior, and Immunity 116 (2024): 286–302. [DOI] [PubMed] [Google Scholar]
  • 33. Jang S. I., Lee M. R., Han J. Y., et al., “A Study of Skin Characteristics With Long‐term Sleep Restriction in Korean Women in Their 40s,” Skin Research and Technology: Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI) 26, no. 2 (2020): 193–199. [DOI] [PubMed] [Google Scholar]
  • 34. Szepietowski J. C., “The Effect of Sunscreens on the Skin Barrier,” Life (Basel) 12, no. 12 (2022): 2083. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Jurkiewicz B. A. and Buettner G. R., “EPR Detection of Free Radicals in UV‐irradiated Skin: Mouse versus human,” Photochemistry and Photobiology 64, no. 6 (1996): 918–922. [DOI] [PubMed] [Google Scholar]
  • 36. Marrot L., “Pollution and Sun Exposure: A Deleterious Synergy. Mechanisms and Opportunities for Skin Protection,” Current Medicinal Chemistry 25, no. 40 (2018): 5469–5486. [DOI] [PubMed] [Google Scholar]
  • 37. Rinnerthaler M., Bischof J., Streubel M. K., et al., “Oxidative Stress in Aging Human Skin,” Biomolecules 5, no. 2 (2015): 545–589. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Zhang J. C., Xia B. J., Wakefield J. S., et al., “The Role and Implications of Epidermal Dysfunction in the Pathogenesis of Inflammaging,” Journal of Investigative Dermatology 13, (2025): S0022‐202X (24) 03034‐3. [DOI] [PubMed] [Google Scholar]
  • 39. Xu F., Yan S., Wu M., et al., “Self‐declared Sensitive Skin in China: A Community‐based Study in Three Top Metropolises,” Journal of the European Academy of Dermatology and Venereology 27, no. 3 (2013): 370–375. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Articles from Skin Research and Technology are provided here courtesy of International Society of Biophysics and Imaging of the Skin, International Society for Digital Imaging of the Skin, and John Wiley & Sons Ltd

RESOURCES