Objective: Recent studies have suggested associations of air pollution exposure with type 1 and type 2 diabetes mellitus (DM). Whether air pollution exposure associated with diagnosis of gestational diabetes mellitus (GDM) was not clear. The objective of this study was to investigate the associations of particulate matter (PM) and gaseous air pollution exposure with diagnosis of GDM. Methods: A total of 11,210 non-diabetic pregnant women were enrolled from a tertiary teaching hospital in Chiayi City, Taiwan between 2006 and 2014. Two-step approach was used for GDM diagnosis. PM2.5 and gaseous air pollution data were obtained from one fixed-site monitoring station (Chiayi City station) operated by Taiwan Environmental Protection Administration. We used multinomial logistic models to estimate the effects of temporal distribution of PM and gaseous pollutants on GDM diagnosis. The models were adjusted for individual-specific effects (nulliparous status, age, body mass index, season, and year) and the moving averages of temperature and relative humidity in the corresponding study period. Results: A total of 705 (6.3%) pregnant women were diagnosed with GDM. PM2.5 during second trimester was 42.3 ± 13.4 ㎍/㎥ After controlling covariates and SO2, NOx, CO and O3, we observed increased odds of GDM with per IQR increase in PM2.5 during the second trimester (OR= 1.88; 95% CI: 1.11, 3.18; OR = 1.60; 95% CI: 1.03, 2.49; OR = 1.97; 95% CI: 1.19, 3.27; OR = 1.98; 95% CI: 1.15, 3.41) in the co-pollutant models. Conclusion: This 9-year cohort study suggested that exposure to air pollution during pregnancy was associated with increased risk of GDM diagnosis using two-step approach in Chiayi City, Taiwan.