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Construction of a nomogram for predicting the risk of allergic rhinitis among employees of long‐distance bus stations in China
Author(s) -
Li Li,
Liu Hang,
Wang Yu,
Han Xu,
Ge Tanxi,
Pan Lijun
Publication year - 2020
Publication title -
indoor air
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.387
H-Index - 99
eISSN - 1600-0668
pISSN - 0905-6947
DOI - 10.1111/ina.12694
Subject(s) - nomogram , relative humidity , medicine , relative risk , cohort , concordance , environmental health , toxicology , veterinary medicine , biology , confidence interval , meteorology , geography
Abstract This study examined indoor air pollutants and their health effects on allergic rhinitis in 3194 employees of 226 bus station halls and then constructed a nomogram model to predict allergic rhinitis risk in those employees. Indoor air temperature, relative humidity, PM 10 , PM 2.5 , total bacteria, and total fungi were measured, and questionnaires were used to collect basic station information and employee health information. The results revealed that the over‐standard rates of PM 10 , PM 2.5 , total bacteria, and total fungi were 18.16%, 31.13%, 2.22%, and 55.89%, respectively. Seasonal variations were found in temperature, relative humidity, and PM 2.5 . Passenger flow could affect temperature, and total bacteria. Central air conditioning could affect total bacteria. A total of 15.90% of the employees were diagnosed as allergic rhinitis by physicians. Relative humidity, fungi, self‐reported allergic rhinitis symptoms, and exposure to smoking were the influencing factors for allergic rhinitis. These four variables were incorporated to construct a nomogram. The concordance index of the nomogram was 0.775 (95% CI: 0.745‐0.806) and 0.749 (95% CI: 0.715‐0.783) for the training cohort and test cohort, respectively. The calibration plot revealed that the nomogram model exhibited good discrimination and consistency. This nomogram model may help predict the occurrence of allergic rhinitis.