Abstract
Growing evidence links ultrafine particles (UFP) to neurotoxicity, but human studies remain limited. Various mobile monitoring approaches have been used to collect repeated short-term air pollution samples and develop human exposure models. However, whether design choices impact epidemiologic inferences, including for UFP and cognitive function, remains unclear.
We evaluated the adjusted association between UFP number concentration (PNC) and late-life cognitive function (Cognitive Abilities Screening Instrument – Item Response Theory [CASI-IRT]) in the Adult Changes in Thought cohort (N=5,283) by leveraging an extensive roadside mobile monitoring campaign specifically designed for epidemiologic application. To assess the impact of common, reduced monitoring approaches on this association, we repeatedly subsampled UFP measures from the extensive campaign, developed exposure models, and evaluated the degree to which associations were impacted.
In a reduced adjustment model, the mean baseline CASI-IRT score decreased by 0.020 (95% CI: -0.036, -0.004) per 1,900 pt/cm³ increase in PNC. Associations were consistent across most sampling designs, including fewer visits (median point estimate -0.019, IQR: -0.022, -0.016), fewer seasons (-0.019, IQR: -0.021, -0.016), and unbalanced sampling (-0.018, IQR: -0.022, -0.016), with very unbalanced designs yielding more variable estimates. In the main model, the CASI-IRT score increased by 0.002 (95% CI: -0.016, 0.020), with similar estimates across fewer visits (0.002, IQR: -0.001, 0.004), fewer seasons (0.000, IQR: -0.001, 0.003), and unbalanced sampling (0.001, IQR: -0.001, 0.004). Rush hour designs were more similar (0.002, IQR: 0.000, 0.003) than business hour designs (0.006, IQR: 0.005, 0.007), but the opposite was true when temporal adjustments were applied (rush: -0.003, IQR: -0.005, -0.001; business: 0.002, IQR: 0.001, 0.004). We observed similar trends in sensitivity and secondary analyses.
We found no link between UFP exposures and late-life cognition. While various monitoring approaches may be used to capture epidemiologic inferences, extending beyond weekday business and rush hours is likely important.
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