Novel Approaches to Air Pollution Exposure and Clinical Outcomes Assessment in Environmental Health Studies

Abstract

An accurate assessment of pollutants’ exposure and precise evaluation of the clinical outcomes pose two major challenges to the contemporary environmental health research. The common methods for exposure assessment are based on residential addresses and are prone to many biases. Pollution levels are defined based on monitoring stations that are sparsely distributed and frequently distanced far from residential addresses. In addition, the degree of an association between outdoor and indoor air pollution levels is not fully elucidated, making the exposure assessment all the more inaccurate. Clinical outcomes’ assessment, on the other hand, mostly relies on the access to medical records from hospital admissions and outpatients’ visits in clinics. This method differentiates by health care seeking behavior and is therefore, problematic in evaluation of an onset, duration, and severity of an outcome. In the current paper, we review a number of novel solutions aimed to mitigate the aforementioned biases. First, a hybrid satellite-based modeling approach provides daily continuous spatiotemporal estimations with improved spatial resolution of 1 × 1 km2 and 200 × 200 m2 grid, and thus allows a more accurate exposure assessment. Utilizing low-cost air pollution sensors allowing a direct measurement of indoor air pollution levels can further validate these models. Furthermore, the real temporal-spatial activity can be assessed by GPS tracking devices within the individuals’ smartphones. A widespread use of smart devices can help with obtaining objective measurements of some of the clinical outcomes such as vital signs and glucose levels. Finally, human biomonitoring can be efficiently done at a population level, providing accurate estimates of in-vivo absorbed pollutants and allowing for the evaluation of body responses, by biomarkers examination. We suggest that the adoption of these novel methods will change the research paradigm heavily relying on ecological methodology and support development of the new clinical practices preventing adverse environmental effects on human health.

The MEDEA childhood asthma study design for mitigation of desert dust health effects: implementation of novel methods for assessment of air pollution exposure and lessons learned

“…Health effects of desert dust exposure are usually assessed by using ecological retrospective data on major outcomes like deaths or hospital admissions and outpatient clinics’ visits [ 8 – 10 , 27 ]. However, data on hospital admissions and outpatient clinics’ visits are influenced by subjective health care seeking behavior and are therefore, problematic in evaluation of the onset, duration and severity of an outcome [ 28 ]. In MEDEA Childhood Asthma panel study, we assess prospectively a range of clinical outcomes in both the control and interventions groups with standard clinical assessment tools like validated clinical symptoms questionnaires, lung function tests and other clinically relevant parameters.…”

Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics

“…Participants without at least four valid days were asked to re-wear devices for an additional seven days. Participants wore devices for an average (minimum - maximum) of 11.8 valid days ( Hajat et al, 2015 ; Mikati et al, 2018 ; Woo et al, 2019 ; Li et al, 2019 ; Bell and Ebisu, 2012 ; Rosofsky et al, 2018 ; Pratt et al, 2015 ; Clark et al, 2014 ; Demetillo et al, 2021 ; Chambliss et al, 2021 ; Jones et al, 2014 ; Di et al, 2017 ; Jbaily et al, 2022 ; Shareck et al, 2014 , 2016 ; Liu et al, 2013 ; Yarza et al, 2020 ; Chaix, 2018 ; Ren et al, 2019 ; Smargiassi et al, 2014 ; Buteau and Goldberg, 2016 ; Languille et al, 2020 ).…”

“…Static measures do not consider total exposure throughout the day or time spent in other locations, limiting the ability to assess daily variations in exposure and potentially under-estimating pollution effects on health ( Shareck et al, 2014 ). Some studies relied on individual pollution sensors to directly measure time-varying exposure to air pollutants ( Liu et al, 2013 ; Yarza et al, 2020 ; Chaix, 2018 ) and related health outcomes such as blood pressure or heart rate variability ( Ren et al, 2019 ; Smargiassi et al, 2014 ; Buteau and Goldberg, 2016 ). However, such studies require a dedicated data collection and can be difficult to implement logistically ( Languille et al, 2020 ).…”

Environmental Health Surveillance System for a Population Using Advanced Exposure Assessment

“…Big data analytics is the process that assists organizations in developing more informed policy by collecting, organizing, and analyzing large quantities of data to search for hidden patterns, unknown correlations, trends, and other useful information [66]. As such, the integration and application of big data analysis is the future for environmental health and an area that urgently requires further development [67].…”