TY - JOUR
T1 - Influence of exposure to climate-related hazards in the phenotypic expression of primary Sjögren’s syndrome
AU - behalf of the Sjögren Big Data Consortium
AU - Flores-Chávez, A.
AU - Brito-Zerón, P.
AU - Ng, W. F.
AU - Szántó, A.
AU - Rasmussen, A.
AU - Priori, R.
AU - Baldini, C.
AU - Armagan, B.
AU - Özkiziltaş, B.
AU - Praprotnik, S.
AU - Suzuki, Y.
AU - Quartuccio, L.
AU - Hernandez-Molina, G.
AU - Inanc, N.
AU - Bartoloni, E.
AU - Rischmueller, M.
AU - Reis-De Oliveira, F.
AU - Fernandes Moça Trevisani, V.
AU - Jurcut, C.
AU - Nordmark, G.
AU - Carubbi, F.
AU - Hofauer, B.
AU - Valim, V.
AU - Pasoto, S. G.
AU - Retamozo, S.
AU - Atzeni, F.
AU - Fonseca-Aizpuru, E.
AU - López-Dupla, M.
AU - Giacomelli, R.
AU - Nakamura, H.
AU - Akasbi, M.
AU - Thompson, K.
AU - Fanny Horváth, I.
AU - Farris, A. D.
AU - Simoncelli, E.
AU - Bombardieri, S.
AU - Kilic, L.
AU - Tufan, A.
AU - Perdan Pirkmajer, K.
AU - Fujisawa, Y.
AU - De Vita, S.
AU - Abacar, K.
AU - Ramos-Casals, M.
N1 - Publisher Copyright:
© Copyright CliniCal and ExpErimEntal rhEumatology 2023.
PY - 2023/12
Y1 - 2023/12
N2 - Objective To analyse how the key components at the time of diagnosis of the Sjögren’s phenotype (epidemiological profile, sicca symptoms, and systemic disease) can be influenced by the potential exposure to climate-related natural hazards. Methods For the present study, the following variables were selected for harmonisation and refinement: age, sex, country, fulfilment of 2002/2016 criteria items, dry eyes, dry mouth, and overall ESSDAI score. Climate-related hazards per country were defined according to the OECD and included seven climate-related hazard types: extreme temperature, extreme precipitation, drought, wildfire, wind threats, river flooding, and coastal flooding. Climatic variables were defined as dichotomous variables according to whether each country is ranked among the ten countries with the most significant exposure. Results After applying data-cleaning techniques and excluding people from countries not included in the OECD climate rankings, the database study analysed 16,042 patients from 23 countries. The disease was diagnosed between 1 and 3 years earlier in people living in countries included among the top 10 worst exposed to extreme precipitation, wildfire, wind threats, river flooding, and coastal flooding. A lower frequency of dry eyes was observed in people living in countries exposed to wind threats, river flooding, and coastal flooding, with a level of statistical association being classified as strong (p<0.0001 for the three variables). The frequency of dry mouth was significantly lower in people living in countries exposed to river flooding (p<0.0001) and coastal flooding (p<0.0001). People living in countries included in the worse climate scenarios for extreme temperature (p<0.0001) and river flooding (p<0.0001) showed a higher mean ESSDAI score in comparison with people living in no-risk countries. In contrast, those living in countries exposed to worse climate scenarios for wind threats (p<0.0001) and coastal flooding (p<0.0001) showed a lower mean ESSDAI score in comparison with people living in no-risk countries. Conclusion Local exposure to extreme climate-related hazards plays a role in modulating the presentation of Sjögren across countries concerning the age at which the disease is diagnosed, the frequency of dryness, and the degree of systemic activity.
AB - Objective To analyse how the key components at the time of diagnosis of the Sjögren’s phenotype (epidemiological profile, sicca symptoms, and systemic disease) can be influenced by the potential exposure to climate-related natural hazards. Methods For the present study, the following variables were selected for harmonisation and refinement: age, sex, country, fulfilment of 2002/2016 criteria items, dry eyes, dry mouth, and overall ESSDAI score. Climate-related hazards per country were defined according to the OECD and included seven climate-related hazard types: extreme temperature, extreme precipitation, drought, wildfire, wind threats, river flooding, and coastal flooding. Climatic variables were defined as dichotomous variables according to whether each country is ranked among the ten countries with the most significant exposure. Results After applying data-cleaning techniques and excluding people from countries not included in the OECD climate rankings, the database study analysed 16,042 patients from 23 countries. The disease was diagnosed between 1 and 3 years earlier in people living in countries included among the top 10 worst exposed to extreme precipitation, wildfire, wind threats, river flooding, and coastal flooding. A lower frequency of dry eyes was observed in people living in countries exposed to wind threats, river flooding, and coastal flooding, with a level of statistical association being classified as strong (p<0.0001 for the three variables). The frequency of dry mouth was significantly lower in people living in countries exposed to river flooding (p<0.0001) and coastal flooding (p<0.0001). People living in countries included in the worse climate scenarios for extreme temperature (p<0.0001) and river flooding (p<0.0001) showed a higher mean ESSDAI score in comparison with people living in no-risk countries. In contrast, those living in countries exposed to worse climate scenarios for wind threats (p<0.0001) and coastal flooding (p<0.0001) showed a lower mean ESSDAI score in comparison with people living in no-risk countries. Conclusion Local exposure to extreme climate-related hazards plays a role in modulating the presentation of Sjögren across countries concerning the age at which the disease is diagnosed, the frequency of dryness, and the degree of systemic activity.
KW - climate
KW - dryness
KW - epidemiology
KW - ESSDAI
KW - Sjögren’s syndrome
KW - systemic
UR - https://www.scopus.com/pages/publications/85181178127
U2 - 10.55563/clinexprheumatol/pmbay6
DO - 10.55563/clinexprheumatol/pmbay6
M3 - Article
C2 - 38019164
AN - SCOPUS:85181178127
SN - 0392-856X
VL - 41
SP - 2437
EP - 2447
JO - Clinical and Experimental Rheumatology
JF - Clinical and Experimental Rheumatology
IS - 12
ER -