Short term associations of weather and air quality with ophthalmic outpatient attendance in eastern China

Abstract The magnitude and timing of short-term associations of weather and air quality with ophthalmic attendance remain poorly quantified. We analysed completed attendances from a tertiary ophthalmology department in Jiangsu, China (2015–2025; 3,788 days) using a time-stratified case-crossover design with conditional Poisson regression. Exposures included catchment-weighted meteorology, nitrogen dioxide (NO₂), and fine particulate matter (PM₂.₅); extreme heat, cold, and heavy rainfall were accumulated over 0–3 and 0–7 days. Over 0–3 days, each additional extreme-heat or heavy-rainfall day was associated with lower completed attendance (rate ratios 0.961 [95% CI 0.954–0.967] and 0.937 [95% CI 0.923–0.952], respectively; both p < 0.0001), whereas extreme cold showed no clear association. From a baseline of 293 visits/day, two heat days and two heavy-rainfall days corresponded to approximately 23 and 36 fewer visits/day, respectively. Lag analyses suggested delayed positive rainfall associations compatible with partial compensation, but no comparable heat pattern within 21 days. The retrospective trigger simulation had 39% precision and 59% recall; approximately 61% of triggered days were false alarms. Locally derived heat thresholds and rainfall amount-related estimates may support preparedness planning. Because completed attendance—not underlying ophthalmic need—was measured, real-time use requires prospective validation of safety, equity, and unmet-need outcomes.