Ambient air pollution has been a worldwide concern with a devastating impact on the health of populations, while increasing the burden on public health systems. Assessing the adverse health effects of air pollution is vital for forming disease control policies. This study investigates the excess risk of 6 air pollutants for 21 disease groups (observed in outpatient visits) through the Poisson regression modeling. Daily air quality data and 1.6 million outpatient visit records from Shenzhen, China are used in the study. The outpatient visits are classified into 21 disease groups according to the International Classification of Diseases, Tenth Revision. The results show that associations between air pollutants and diseases vary across different disease groups. Specifically, the following disease classes are significantly associated with air pollution: blood, metabolic, ophthalmological, circulatory, respiratory, digestive, musculoskeletal, connective tissue, and genitourinary diseases. Nitrogen dioxide, particulate matter less than 10 μm in diameter (PM10), particulate matter less than 2.5 μm in diameter (PM2.5), and air quality index have the most extensive impact on more than ten disease groups. A health effect graph is built to support public health management decision-making and provide residents with information about health effects of air pollution.