RESUMO
OBJECTIVES: To analyse how the potential exposure to air pollutants can influence the key components at the time of diagnosis of Sjögren's phenotype (epidemiological profile, sicca symptoms, and systemic disease). METHODS: For the present study, the following variables were selected for harmonization and refinement: age, sex, country, fulfilment of 2002/2016 criteria items, dry eyes, dry mouth, and overall ESSDAI score. Air pollution indexes per country were defined according to the OECD (1990-2021), including emission data of nitrogen and sulphur oxides (NO/SO), particulate matter (PM2.5 and 1.0), carbon monoxide (CO) and volatile organic compounds (VOC) calculated per unit of GDP, Kg per 1000 USD. RESULTS: The results of the chi-square tests of independence for each air pollutant with the frequency of dry eyes at diagnosis showed that, except for one, all variables exhibited p-values <0.0001. The most pronounced disparities emerged in the dry eye prevalence among individuals inhabiting countries with the highest NO/SO exposure, a surge of 4.61 percentage points compared to other countries, followed by CO (3.59 points), non-methane (3.32 points), PM2.5 (3.30 points), and PM1.0 (1.60 points) exposures. Concerning dry mouth, individuals residing in countries with worse NO/SO exposures exhibited a heightened frequency of dry mouth by 2.05 percentage points (p<0.0001), followed by non-methane exposure (1.21 percentage points increase, p=0.007). Individuals inhabiting countries with the worst NO/SO, CO, and PM2.5 pollution levels had a higher mean global ESSDAI score than those in lower-risk nations (all p-values <0.0001). When systemic disease was stratified according to DAS into low, moderate, and high systemic activity levels, a heightened proportion of individuals manifesting moderate/severe systemic activity was observed in countries with worse exposures to NO/SO, CO, and PM2.5 pollutant levels. CONCLUSIONS: For the first time, we suggest that pollution levels could influence how SjD appears at diagnosis in a large international cohort of patients. The most notable relationships were found between symptoms (dryness and general body symptoms) and NO/SO, CO, and PM2.5 levels.