Ambient particulate matter and paramedic assessments of acute diabetic, cardiovascular, and respiratory conditions

Background: Ambulance data provide a useful source of population-based and spatiotemporally resolved information for assessing health impacts of air pollution in non-hospital settings. We used the clinical records of paramedics to quantify associations between PM_2.5 and diabetic, cardiovascular, and respiratory conditions commonly managed by those responding to calls for emergency ambulance services.

Methods: We evaluated 394,217 paramedic assessments from three states in Southeastern Australia (population 13.2 million) and daily PM_2.5 concentrations modeled at 5km resolution from 2009-2014. We used a time-stratified, case-crossover analysis adjusted for daily meteorology to estimate the odds ratios and 95% confidence intervals for each clinical outcome per 10 µg/m³ increase in daily PM_2.5 at lags from 0 to 2 days.

Results: Increased PM_2.5 was associated with increased odds of paramedic assessments of hypoglycemia (OR1.07, 95%CI1.02-1.12, lag 0), arrhythmia (OR1.05, 95%CI 1.02-1.09, lag 0), heart failure (OR1.07, 95%CI 1.02-1.12, lag 1), faint (OR1.09, 95%CI 1.04-1.13, lag 0), asthma (OR1.06, 95%CI 1.01-1.11, lag 1), chronic obstructive pulmonary disease (OR1.07, 95%CI 1.01-1.13, lag 1), and croup (OR1.09, 95%CI 1.02-1.17). We did not identify associations with cerebrovascular outcomes.

Conclusions: Ambulance data enable the evaluation of important clinical syndromes that are often initially managed in non-hospital settings. Daily PM_2.5 was associated with hypoglycemia,faint, and croup in addition to the respiratory and cardiovascular outcomes that are better established.