Ambient Particulate Matter and Paramedic Assessments of Acute Diabetic, Cardiovascular, and Respiratory Conditions.

Abstract

Ambulance data provide a useful source of population-based and spatiotemporally resolved information for assessing health impacts of air pollution in nonhospital settings. We used the clinical records of paramedics to quantify associations between particulate matter (PM2.5) and diabetic, cardiovascular, and respiratory conditions commonly managed by those responding to calls for emergency ambulance services. We evaluated 394,217 paramedic assessments from three states in Southeastern Australia (population 13.2 million) and daily PM2.5 concentrations modeled at 5 km resolution from 2009 to 2014. We used a time-stratified, case-crossover analysis adjusted for daily meteorology to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for each clinical outcome per 10 µg/m increase in daily PM2.5 at lags from 0 to 2 days. Increased PM2.5 was associated with increased odds of paramedic assessments of hypoglycemia (OR = 1.07; 95% CI = 1.02, 1.12, lag 0), arrhythmia (OR = 1.05; 95% CI = 1.02, 1.09, lag 0), heart failure (OR = 1.07; 95% CI = 1.02, 1.12, lag 1), faint (OR = 1.09; 95% CI = 1.04-1.13, lag 0), asthma (OR = 1.06; 95% CI = 1.01, 1.11, lag 1), chronic obstructive pulmonary disease (OR = 1.07; 95% CI = 1.01, 1.13, lag 1), and croup (OR = 1.09; 95% CI = 1.02, 1.17). We did not identify associations with cerebrovascular outcomes. Ambulance data enable the evaluation of important clinical syndromes that are often initially managed in nonhospital settings. Daily PM2.5 was associated with hypoglycemia, faint, and croup in addition to the respiratory and cardiovascular outcomes that are better established.