Today, air pollution remains a significant issue, particularly in high-altitude areas where its impact on respiratory disease remains incompletely explored. This study aims to investigate the association between various air pollutants and outpatient visits for respiratory disease in such regions, specifically focussing on Xining from 2016 to 2021. By analysing over 570,000 outpatient visits using a time-stratified case-crossover design and conditional logistic regression, we assessed the independent effects of pollutants like PM 2.5 , PM 10 , SO 2 , NO 2 , and CO, as well as their interactions. The evaluation of interactions employed measures such as relative excess odds due to interaction (REOI), attributable proportion due to interaction (AP), and synergy index (S). We also conducted a stratified analysis to identify potentially vulnerable populations. Our findings indicated that exposure to PM 2.5 , PM 10 , SO 2 , NO 2 , and CO significantly increased outpatient visits for respiratory disease, with odds ratios (ORs) of 2.40 % (95 % CI: 2.05 %, 2.74 %), 1.07 % (0.98 %, 1.16 %), 3.86 % (3.23 %, 4.49 %), 4.45 % (4.14 %, 4.77 %), and 6.37 % (5.70 %, 7.04 %), respectively. However, exposure to O 3 did not show a significant association. We found significant interactions among PM 2.5 , SO 2 , NO 2 , and CO, where combined exposure further exacerbated the risk of respiratory diseases. For example, in the combination of PM 2.5 and SO 2 , the REOI, AP, and S were 0.07 (95 % CI: 0.06, 0.09), 0.07 (0.06, 0.07), and 1.07 (1.05, 1.09), respectively. Additionally, elderly individuals and females were more sensitive to these pollutants, but no statistically significant interaction effects were observed between different age and gender groups. In conclusion, our study highlights the strong link between air pollution and respiratory disease in high-altitude areas, with combined pollutant exposure posing an even greater risk. It underscores the need for enhanced air quality monitoring and public awareness campaigns, particularly to protect vulnerable populations like the elderly and females.