Assessing exposure metrics for PM and birth weight models

The link between air pollution exposure and adverse birth outcomes is of public health concern due to the relationship between poor pregnancy outcomes and the onset of childhood and adult diseases. As personal exposure measurements are difficult and expensive to obtain, proximate measures of air pollution exposure are traditionally used. We explored how different air pollution exposure metrics affect birthweight regression models. We examined the effect of maternal exposure to ambient levels of particulate matter <10, <2.5 μm in aerodynamic diameter (PM10, PM2.5) on birthweight among infants in North Carolina. We linked maternal residence to the closest monitor during pregnancy for 2000–2002 (n=350,754). County-level averages of air pollution concentrations were estimated for the entire pregnancy and each trimester. For a finer spatially resolved metric, we calculated exposure averages for women living within 20, 10, and 5 km of a monitor. Multiple linear regression was used to determine the association between exposure and birthweight, adjusting for standard covariates. In the county level model, an interquartile increase in PM10 and PM2.5 during the entire gestational period reduced birthweight by 5.3 g (95% CI: 3.3 – 7.4) and 4.6 g (95% CI: 2.3 – 6.8), respectively. This model also showed a reduction in birthweight for PM10 (7.1 g, 95% CI: 1.0–13.2) and PM2.5 (10.4 g, 95% CI: 6.4 – 14.4) during the third trimester. Proximity models for 20, 10, and 5 km distances showed similar results to the county level models. County level models assume that exposure is spatially homogeneous over a larger surface area than proximity models. Sensitivity analysis demonstrated that at varying spatial resolutions, there is still a stable and negative association between air pollution and birthweight, despite North Carolina’s consistent attainment of federal air quality standards.