PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis. (April 2020)

• Record Type: Journal Article
• Authors: Evangelopoulos, Dimitris; Katsouyanni, Klea; Keogh, Ruth H.; Samoli, Evangelia; Schwartz, Joel; Barratt, Ben; Zhang, Hanbin; Walton, Heather
• Is Part Of: Environment international. Volume 137(2020)
• Publication Date: 2020-04
• Subjects: Environmental protection -- Periodicals; Environmental health -- Periodicals; Environmental monitoring -- Periodicals; Environmental Monitoring -- Periodicals; Environnement -- Protection -- Périodiques; Hygiène du milieu -- Périodiques; Environnement -- Surveillance -- Périodiques; Environmental health; Environmental monitoring; Environmental protection; Periodicals; 333.705
• DOI: 10.1016/j.envint.2020.105500
• Languages: English
• ISSNs: 0160-4120

Abstract

Highlights: Studies with information on PM2.5 and NO2 measurement error structures were reviewed. We derived outdoor source personal exposure to compare with ambient concentrations. Outdoor sources contribute 44% to total personal exposure to PM2.5 and 74% for NO2 . Mean difference (measurement error) was 5.72 μg/m 3 for PM2.5 and 7.17 ppb for NO2 . Error variability was also greater for NO2 . Error correlation was not reported. Abstract: Background: The use of proxy exposure estimates for PM2.5 and NO2 in air pollution studies instead of personal exposures, introduces measurement error, which can produce biased epidemiological effect estimates. Most studies consider total personal exposure as the gold standard. However, when studying the effects of ambient air pollution, personal exposure from outdoor sources is the exposure of interest. Objectives: We assessed the magnitude and variability of exposure measurement error by conducting a systematic review of the differences between personal exposures from outdoor sources and the corresponding measurements for ambient concentrations in order to increase understanding of the measurement error structures of the pollutants. Data sources and eligibility criteria: We reviewed the literature (ISI Web of Science, Medline, 2000–2016) for English language studies (in any age group in any location (NO2 ) or Europe and North America (PM2.5 )) that reported repeated measurements over time both for personal and ambient PM2.5 or NO2 concentrations. Only a few studies reported personal exposure from outdoor sources. We also collected data for infiltration factors and time-activity patterns of the individuals in order to estimate personal exposures from outdoor sources in every study. Study appraisal and synthesis methods: Studies using modelled rather than monitored exposures were excluded. Type of personal exposure monitor was assessed. Random effects meta-analysis was conducted to quantify exposure error as the mean difference between "true" and proxy measures. Results: Thirty-two papers for PM2.5 and 24 for NO2 were identified. Outdoor sources were found to contribute 44% (range: 33–55%) of total personal exposure to PM2.5 and 74% (range: 57–88%) to NO2 . Overall estimates of personal exposure (24-hour averages) from outdoor sources were 9.3 μg/m 3 and 12.0 ppb for PM2.5 and NO2 respectively, while the corresponding difference between these exposures and the ambient concentrations (i.e. the measurement error) was 5.72 μg/m 3 and 7.17 ppb. Our findings indicated also higher error variability for NO2 than PM2.5 . Large heterogeneity was observed which was not explained sufficiently by geographical location or age group of the study sample. Limitations, conclusions and implications of key findings: Relying only on information available in published studies led to some limitations: the contribution of outdoor sources to total personal exposure for NO2 had to be inferred, individual variation in exposure misclassification was unavailable and instrument error could not be addressed. The larger magnitude and variability of errors for NO2 compared with PM2.5 has implications for biases in the health effect estimates of multi-pollutant epidemiological models. Results suggest that further research is needed regarding personal exposure studies and measurement error bias in epidemiological models.