From measures to models: an evaluation of air pollution exposure assessment for epidemiological studies of pregnant women

• Published in: Occupational and environmental medicine (London, England) England), 2008-09, Vol.65 (9), p.579-586
• Main Authors: Nethery, E, Leckie, S E, Teschke, K, Brauer, M
• Format: Article
• Language: English
• Subjects: Adult; Air; Air Pollutants - analysis; Air pollution; Air Pollution - statistics & numerical data; Biological and medical sciences; Canada - epidemiology; Codes; Correlations; Environment. Living conditions; Environmental Monitoring - methods; Environmental pollutants toxicology; Epidemiological Monitoring; Epidemiology; Estimates; Estimation methods; Female; Global positioning systems; GPS; Humans; Inhalation Exposure - statistics & numerical data; Land use; Logistic Models; Lurs; Maternal Exposure - statistics & numerical data; Medical sciences; Modeling; Nitric Oxide - analysis; Nitrogen dioxide; Nitrogen Dioxide - analysis; Outdoor air quality; Particle Size; Particulate matter; Pollutants; Pregnancy; Public health. Hygiene; Public health. Hygiene-occupational medicine; Spatial models; Spatial variability; Statistical variance; Toxicology; Traffic estimation
• ISSN: 1351-0711; 1470-7926
• DOI: 10.1136/oem.2007.035337

Objectives:To evaluate exposure estimation methods such as spatially resolved land-use regression models and ambient monitoring data in the context of epidemiological studies of the impact of air pollution on pregnancy outcomes.Methods:The study measured personal 48 h exposures (NO, NO2, PM2.5 mass and absorbance) and mobility (time activity and GPS) for 62 pregnant women during 2005–2006 in Vancouver, Canada, one to three times during pregnancy. Measurements were compared to modelled (using land-use regression and interpolation of ambient monitors) outdoor concentrations at subjects’ home and work locations.Results:Personal NO and absorbance (ABS) measurements were moderately correlated (NO: r = 0.54, ABS: r = 0.29) with monitor interpolations and explained primarily within-subject (temporal) variability. Land-use regression estimates including work location improved correlations for NO over those based on home postal code (for NO: r = 0.49 changed to NO: r = 0.55) and explained more between-subject variance (4–20%); limiting to a subset of samples (n = 61) when subjects spent >65% time at home also improved correlations (NO: r = 0.72). Limitations of the GPS equipment precluded assessment of including complete GPS-based mobility information.Conclusions:The study found moderate agreement between short-term personal measurements and estimates of ambient air pollution at home based on interpolation of ambient monitors and land-use regression. These results support the use of land-use regression models in epidemiological studies, as the ability of such models to characterise high resolution spatial variability is “reflected” in personal exposure measurements, especially when mobility is characterised.