Climatic variables are associated with seasonal acute asthma admissions to accident and emergency room facilities in Trinidad, West Indies

Abstract

Objectives: To determine if there is seasonal variation in acute asthmatic visits to accident and emergency (A&E) facilities in Trinidad and to identify the climatic variables associated with such visits.

Design and methods: A retrospective census of patients with asthma, defined as those who required emergency bronchodilator nebulization, was taken at two A&E facilities in Trinidad from 1 January 1997 to 31 December 1999. The study included patients aged 64 years and under. Patient demographic data were obtained from the A&E records. Climate variables were taken from the island's sole Meteorological Office. Multiple regression was used to identify climate variables that were independent predictors of A&E asthma visits.

Results: There were a total of 45 842 asthma admissions to the two facilities during the study period. Visits exhibited a cyclic pattern over the 3 years that varied according to the island's dry (January-May) and wet (June-December) seasons. There were more visits during the wet season than the dry (40 [SD=2] vs. 32 [SD=2] visits/day; P<0.001). The results of multiple regression indicated that season (P<0.001), barometric pressure (P<0.001), temperature difference (P<0.001), minimum temperature2 (P<0.001) and wind speed2 (P=0.032) were predictors of paediatric visits. Independent predictors of adult visits were season (P<0.001), relative humidity (P<0.001), minimum temperature (P=0.01), temperature difference2 (P<0.001) and minimum temperature2 (P=0.004). Season and climatic variables explained 18% of the variance of the total A&E asthma admissions.

Conclusion: There is seasonal variation in acute asthma visits to A&E facilities in Trinidad, which remains significant after controlling for climate variables. However, while climate has a role, there are other factors that may also be responsible for increased visits during the wet season. More research is needed to identify these factors.