As gestational diabetes mellitus (GDM) rises as a major public health concern, various factors have been identified as potential contributors, with air pollution drawing increasing attention. The mechanisms by which air pollutants lead to detrimental impacts are largely attributed to oxidative stress. However, the role of air pollution is still not entirely clarified, suggesting that additional factors, such as genetic variability, particularly of genes involved in redox homeostasis, influence the GDM risk. This study addresses three questions: (1) whether ambient PM_2.5, PM₁₀, O₃, and NO₂ exposures associate with GDM risk; (2) if GSTM1-/GSTT1-null genotypes affect the risk of GDM; and (3) whether these genotypes modify pollution–GDM associations. This case–control study comprised 133 women in the case group and 144 in the control group. Exposure to air pollutants was assessed based on the participants’ residential addresses and during different time windows: pre-pregnancy period, first trimester, and second trimester. GSTM1/GSTT1 genotyping was conducted from blood samples. Higher PM_2.5, PM₁₀, and O₃ levels increased GDM risk in women. While GSTM1-/GSTT1-null genotypes showed no overall link to GDM, non-smokers with GSTM1-null had higher GDM risk when exposed to PM_2.5 during the first trimester. While further research on gene–environment interactions is needed, our findings highlight that reducing air pollution may lower GDM risk.

In regions with sustained air pollution, the adoption of protective health behaviors is critical, particularly among pregnant women—a population marked by physiological vulnerability and heightened receptivity to preventive guidance. Understanding and supporting patient-driven behavioral change requires attention to individual perception and awareness, which are shaped by socio-economic and spatial factors, as well as access to credible information. Objectives: This study investigates how pregnant women in Serbia perceive air quality, identifies determinants that influence these perceptions, and evaluates the extent and nature of behavioral adaptations undertaken to mitigate exposure-related risks. Methods: A cross-sectional survey was conducted among 279 pregnant women using a structured, researcher-administered questionnaire. Collected data included demographic and psychosocial variables, air quality perceptions, self-reported health effects, and behavioral responses. Residential proximity to land-use attributes was assessed using GIS-based spatial analysis. Results: Most participants perceived air quality as poor (68.8%), primarily informed by unofficial sources such as mobile applications and social media. Living close to continuous urban fabric (OR = 0.180, 95% CI: 0.059–0.558, p = 0.003) and water (OR = 0.306, 95% CI: 0.127–0.738, p = 0.008) was associated with poorer perceptions, while proximity to forests (OR = 2.938, 95% CI: 1.323–6.525, p = 0.008) correlated with more favorable assessments. Despite prevalent concern, around half of respondents (50.2%) reported no behavioral modifications. Importantly, none had received guidance from healthcare professionals on the topic. Conclusions: These findings highlight critical gaps in environmental health literacy and provider engagement. Integrating tailored communication and behavioral support in existing prenatal counseling could advance health-related quality of life in this vulnerable population.