Resumen
Eleven years of hospital admissions data for Auckland, New Zealand for respiratory conditions are analyzed using a Poisson regression modelling approach, incorporating a spline function to represent time, based on a detailed record of haze events and surface air pollution levels over an eleven-year period, taking into account the daily average temperature and humidity, the day of the week, holidays and trends over time. NO2 was the only pollutant to show a statistically significant increase (p = 0.009) on the day of the haze event for the general population. Ambient concentrations of CO, NO and NO2 were significantly associated with admissions with an 11-day lag period for the 0?14 year age group and a 5?7 day lag period for the 65+ year age group. A 3-day lag period was found for the 15?64 year age group for CO, NO and PM10. Finally, the incidence of brown haze was linked to significant increases in hospital admissions. A lag period of 5 days was recorded between haze and subsequent increases in admissions for the 0?14 year age group and the 65+ group and an 11-day lag for the 15?64 year age group. The results provide the first statistical link between Auckland brown haze events, surface air pollution and respiratory health. Medical institutions and practitioners could benefit from improved capacity to predict Auckland?s brown haze events in order prepare for the likely increases in respiratory admissions over the days ahead.