Estimating long-term average household air pollution concentrations from repeated short-term measurements in the presence of seasonal trends and crossover

Estimating long-term exposure to household air pollution is essential for quantifying health effects of chronic exposure and the benefits of intervention strategies. However, typically only a small number of short-term measurements are made. We compare different statistical models for combining these short-term measurements into predictions of a long-term average, with emphasis on the impact of temporal trends in concentrations and crossover in study design. We demonstrate that a linear mixed model that includes time adjustment provides the best predictions of long-term average, which have lower error than using household averages or mixed models without time, for a variety of different study designs and underlying temporal trends. In a case study of a cookstove intervention study in Honduras, we further demonstrate how, in the presence of strong seasonal variation, long-term average predictions from the mixed model approach based on only two or three measurements can have less error than predictions based on an average of up to six measurements. These results have important implications for the efficiency of designs and analyses in studies assessing the chronic health impacts of long-term exposure to household air pollution.

Automated summary

Estimating long-term exposure to household air pollution is crucial for quantifying the health effects of chronic exposure and intervention strategies. This study compares different statistical models for predicting long-term averages based on short-term measurements, emphasizing the influence of temporal trends and study design. The results show that a linear mixed model with time adjustment provides the most accurate long-term average predictions, outperforming household averages or mixed models without time adjustment. These findings have important implications for designing and analyzing studies on the chronic health impacts of long-term exposure to household air pollution.