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Journal of Clinical & Experimental Dermatology Research

Journal of Clinical & Experimental Dermatology Research
Open Access

ISSN: 2155-9554

+44 1478 350008

Abstract

Prevalence and Risk Factors of Sensitive Skin Syndrome in Hong Kong Using the Validated Sensitive Scale-10 (SS-10) Questionnaire: A Community Epidemiological Survey

Kam Tim Michael Chan* and Amy Ho Nam Cheung

Background: This community-based epidemiological study aimed to estimate the prevalence and risk factors of sensitive skin syndrome (SSS) using the validated Sensitive Scale-10 (SS-10) questionnaire in Hong Kong.

Methods: In January 2018, 500 subjects were recruited (quota sampling method) across five Hong Kong districts from high to lower level of pollutions (Mong Kok, Tsim Sha Tsui, Causeway Bay, Tsuen Wan, and Shatin; n=100 each). Face-to-face interviews were conducted by volunteers without prior knowledge on sensitive skin definition. Each participant filled out a questionnaire containing information on demography, concomitant skin diseases, and SS-10. Prevalence estimation was based on the cutoff value developed on clinical data in Hong Kong. Risk factors of sensitive skin were analysed using multiple linear regression modelling with total score of SS-10 as the outcome variable.

Results: Our study reported a prevalence of 11.4% of sensitive skin in the local community sample, with skin conditions and districts as significant predictors. The model accounted for 67.6% variance of the total SS-10 score and significantly differed from the null model: F (10, 489)=101.95, p<0.001 with an effect size of 2.09. Significant predictors of sensitive skin included eczema (β=17.02, p<.001), urticaria (β=15.48, p<0.001), psoriasis (β=19.86, p<0.001), food allergy-induced skin sensitivity (β=7.00, p<0.001), and cosmetics-induced skin sensitivity (β=14.84, p<0.001). Tsim Sha Tsui (TST) predicted skin sensitivity significantly (β=6.46, p<0.001) with reference to Shatin.

Conclusion: Our study reported a lower prevalence of SSS in Hong Kong. Suggested predictors were skin conditions, crowded and polluted districts, food allergies, and cosmetics.

Published Date: 2019-11-25; Received Date: 2019-11-05

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