# Ambient air pollution and psoriasis: a nationwide cross-sectional study of 149 744 Chinese patients in 31 provinces

## TL;DR

This study finds that air pollution is linked to higher rates of psoriasis in China, offering insights for public health policies.

## Contribution

The study provides novel evidence on the association between ambient air pollution and psoriasis prevalence in a large Asian population.

## Key findings

- PM10, PM2.5, AQI, and NO2 show significant positive correlations with psoriasis prevalence.
- Combined effects of pollutants like PM2.5 and SO2 strongly influence psoriasis subtypes.
- Pollutants exhibit spatial heterogeneity and clustering patterns across Chinese provinces.

## Abstract

Skin is the largest organ of the human body. It continuously encounters environmental toxicants, including airborne pollutants, which may induce many skin disorders, such as psoriasis. However, evidence on the association between airborne pollutants and psoriasis prevalence in China remains limited.

We used nationwide inpatient diagnostic data on psoriasis from 2021 to 2023, encompassing 149 744 cases across 31 provinces, municipalities, and autonomous regions in China, along with corresponding air pollution data. We analysed the spatial distribution and clustering patterns of psoriasis using the spatial autocorrelation analysis. We employed Pearson correlation analysis and Geodetector to explore the spatial heterogeneity of psoriasis and its association with airborne pollutants at the provincial level. We assessed the explanatory power of individual airborne pollutants and their combined effects on psoriasis prevalence.

Pearson correlation analysis revealed that PM10 (r = 0.604), PM2.5 (r = 0.429), air quality index (AQI) (r = 0.542), and NO2 (r = 0.476) have significant positive correlations with psoriasis prevalence. Psoriasis and its subtypes exhibited significant spatial heterogeneity and diverse clustering patterns across regions. Geodetector identified PM10 (q = 0.357; P = 0.000), AQI (q = 0.315; P = 0.000), and O3 (q = 0.264; P = 0.000) as key contributors to this spatial heterogeneity. Interactive detection analysis further revealed that the combined effects of specific pollutant pairs, including PM2.5 and SO2 (q = 0.790), PM10 and SO2 (q = 0.727), as well as O3 and SO2 (q = 0.704), played a pivotal role in explaining the prevalence of psoriasis. The other combinations also showed an important impact on psoriasis subtypes, including psoriasis vulgaris (PM2.5 and SO2) (q = 0.792), psoriasis erythematous (PM2.5 and SO2) (q = 0.852), psoriatic arthritis (PM10 and O3) (q = 0.840), and nail psoriasis (PM10 and O3) (q = 0.789).

The airborne pollutants influence psoriasis prevalence and its subtypes. With the largest global study of the Asian population, we provide novel insights into the impact of air pollution on psoriasis, guiding future public health policies and clinical interventions.