Times trends of atopic dermatitis among the Chinese population, 1990-2019: a joinpoint and Bayesian age-period-cohort analysis
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1
Guangzhou University of Chinese Medicine, China
2
Department of Mathematics - Science Studies, Guangzhou University of Chinese Medicine, China
Publication date: 2023-04-27
Popul. Med. 2023;5(Supplement):A1839
ABSTRACT
Background: Atopic dermatitis (AD) is a chronic inflammatory skin condition, which has become a serious public health problem and has the highest disease burden among skin diseases. Objectives: This study investigates the independent effects of age, period, and cohort on the AD prevalence from 1990 to 2019 in China, compares these effects by gender, and then predicts the future burden over the next decade. Methods: Data were obtained from the Global Burden of Disease, Injuries, and Risk Factors Study 2019 (GBD 2019). We used Joinpoint regression model to calculate the annual percentage change (APC) in AD prevalence, the age-period-cohort analysis (APC) to estimate the independent effects of age, period, and cohort, the Bayesian age-period-cohort model to predict the epidemic of AD in 2020-2030. Results: In 2019, there were 35.58 million cases of AD in China, with an age-standardized prevalence rate (ASPR) of 2460.183 (per 100000 population), 1847.290 (per 100,000 population), and 3097.672 (per 100,000 population) in both sex, men, and women, respectively. From 1990 to 2019, the ASPR of AD fluctuant. The periods of 2017-2019 were "joinpoint" for men and women (APC: 7.1% and 4.0%). The age-period-cohort analyses showed that the prevalence of AD was associated with age, being higher in the 1 to 4 years old, 90 to 94 years old, and 95 + years age groups. The cohort effect generally peaked in the cohort born in 2015-2019. Within 2030, the age-standardized incidence rate of AD was projected to be 8.8 and 5.9 in men and women, respectively. Conclusions: Substantial variations exist in AD burden between males and females, and in age groups. Given the increasing AD burden in China, researchers should pay attention to AD, and help policymakers identify modifiable risk factors to take targeted measures to reduce the AD burden, particularly in children and older adults.