Modeling Desert Dust Exposures in Epidemiologic Short-term Health Effects Studies

Desert dust is assumed to have substantial adverse effects on human health. However, the epidemiologic evidence is still inconsistent, mainly because previous studies used different metrics for dust exposure and its corresponding epidemiologic analysis. We aim to provide a standardized approach to the methodology for evaluating the short-term health effects of desert dust.

We reviewed the methods commonly used for dust exposure assessment, from use of a binary metric for the occurrence of desert dust advections to a continuous one for quantifying particulate matter attributable to desert dust. We presented alternative time-series Poisson regression models to evaluate the dust exposure-mortality association, from the underlying epidemiological and policy-relevant questions. A set of practical examples, using a real dataset from Rome, Italy, illustrate the different modeling approaches.

We estimate substantial effects of desert dust episodes and particulate matter with diameter <10 μm (PM10) on daily mortality. The estimated effect of non-desert PM10 was 1.8% (95% confidence interval [CI] = 0.4, 3.2) for a 10 μg/m rise of PM10 at lag 0 for dust days, 0.4% (95% CI = -0.1, 0.8) for non-dust days, and 0.6% (95% CI = -0.5, 2.1) for desert PM10.

The standardized modeling approach we propose could be applicable elsewhere, in and near hot spots, which could lead to more consistent evidence on the health effects of desert dust from future studies.