Assessing the Exposome with External Measures: Commentary on the State of the Science and Research Recommendations

Abstract

The exposome comprises all environmental exposures that a person experiences from conception throughout the life course. Here we review the state of the science for assessing external exposures within the exposome. This article reviews (a) categories of exposures that can be assessed externally, (b) the current state of the science in external exposure assessment, (c) current tools available for external exposure assessment, and (d) priority research needs. We describe major scientific and technological advances that inform external assessment of the exposome, including geographic information systems; remote sensing; global positioning system and geolocation technologies; portable and personal sensing, including smartphone-based sensors and assessments; and self-reported questionnaire assessments, which increasingly rely on Internet-based platforms. We also discuss priority research needs related to methodological and technological improvement, data analysis and interpretation, data sharing, and other practical considerations, including improved assessment of exposure variability as well as exposure in multiple, critical life stages.

Keywords: exposome; external exposures; geographic information systems; global positioning systems; remote sensing; smartphones.

Figure 1:

Conceptual model for the assessment of environmental exposures. Abbreviations: ETS, environmental tobacco smoke; GIS, geographic information systems; PBPK, physiologically based pharmacokinetic models; UV, ultraviolet. (Adapted from Reference , figure 1.5, p. 12, by permission of Oxford University Press, https://global.oup.com/academic/?lang=en&cc=us.)

Figure 2:

Three-dimensional profile of the Global System for Mobile Communication (GSM) (top panel) and Universal Mobile Telecommunications System (UMTS) (bottom panel) electric field strengths [volts per meter (V m⁻²)]. The yellow triangles show the locations of GSM and UMTS antennas for the top and bottom panels, respectively. Reprinted from Sci. Total Environ., 445–46, Beekhuizen J, Vermeulen R, Kromhout H, Burgi A, Huss A, Geospatial modeling of electromagnetic fields from mobile phone base stations, 202–9, 2013, with permission from Elsevier.

Figure 3:

Global decadal (2001–2010) satellite-derived mean PM_2.5 concentrations (adapted from Reference 99).

Figure 4:

Spatial pattern of exposure (yellow) to electromagnetic fields from GSM base stations during travel by train, tram, and bus. The height of the yellow profile is proportional to the electric field strength (1 km represents 1 V m⁻²). Courtesy © 2011 Google, © 2011 Aerodata International Surveys, © 2011 Europa Technologies, © 2011 TeleAtlas. Reprinted from Environ. Int., 48, Bolte JFB, Eikelboom T, Personal radiofrequency electromagnetic field measurements in the Netherlands: exposure level and variability for everyday activities, times of day and types of area, 113–42, 2012, with permission from Elsevier.

Figure 5:

The changing paradigm of air pollution monitoring (adapted with permission from Reference . Copyright 2013 American Chemical Society).

Figure 6:

Personal levels of noise (dBA), ultraviolet B (UVB) (mJ/cm²), humidity (%), temperature (°C), black carbon (BC) (μg/m³), blood pressure (mmHg), heart rate variability (HRV) (ms), heart beat (beats per minute), lung function (L), emotional status, and physical activity (PA) [metabolic equivalents (METs) during two 24-h periods] (adapted from Reference 67).

Figure 7:

Examples of silicone personal sampling samplers. (a) Configurations of wristbands used in the study including a single wristband, one cut and worn as a lapel, and one worn as a stacked wristband in which only the outer band was analyzed; (b–c) bags used for transport that were attached to track participant identification and exposure time in the occupational deployments; (d) single wristband deployment (debossed writing as pictured: “OSU EINOME” for Oregon State University Environmental Integrated Organic Monitor of Exposure) (adapted from 71).

Figure 8:

An off-the-shelf iPhone 4, representative of the growing class of sensor-enabled phones. This phone includes eight different sensors: accelerometer, global positioning system (GPS), ambient light, dual microphones, proximity sensor, dual cameras, compass, and gyroscope. © 2010 IEEE. Reprinted, with permission, from Reference .

Figure 9:

On-body sensor technology allows data collection for individual, (near) real-time, care-driven monitoring of health-related end points. Reprinted from Int. J. Hyg. Environ. Health, 217(8), Smolders R, de Boever P, Perspectives for environment and health research in Horizon 2020: Dark ages or golden era?, 891–96, 2014, with permission from Elsevier.