Short-term exposure to PM_2.5 and its components and neuropsychiatric hospitalizations in Delhi, India

Despite being one of the most polluted cities globally, evidence on the neuropsychiatric impacts of air pollution in Delhi using primary data remains limited. This study aimed to assess the association between neuropsychiatric hospitalization and exposure to PM_2.5 and its chemical components.

Using a data fusion technique, ground-based PM_2.5 concentrations were integrated with high-resolution (5 km × 5 km) gridded WRF-Chem-simulated PM_2.5 data to generate a fused concentration dataset for the period 2016-2019. The patients' data hospitalized for neuropsychiatric disorders were collected from the hospital. A time-series study design was employed, using a generalized additive model integrated with a distributed lag model (GAM-DLM) to estimate the associations.

PM_2.5 exposure was significantly associated with increased neuropsychiatric hospitalizations, with a 0.926% (95% CI: 0.097-1.762) increase per 10 μg/m³ increment. Among components, black carbon (BC) showed the strongest association (11.509%, 95% CI: 3.272-20.402), compared to organic carbon (OC) and other inorganics (OIN). Higher risks were observed among females and individuals aged 15-60 years, although the differences between gender and age groups were not statistically significant. Among disorders, only anxiety disorders showed a statistically significant association. Among all the source-specific PM_2.5 contributions, only the industrial-PM_2.5 was significantly associated with hospitalization.

Short-term exposure to PM_2.5, BC, and OC was associated with increased neuropsychiatric hospitalizations. These findings highlight the importance of considering PM_2.5 chemical composition and emission sources, in addition to mass concentration, in air quality management.