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Exposure assessment for air pollution epidemiology: A scoping review of emerging monitoring platforms and designs.
Kim, Sun-Young; Blanco, Magali N; Bi, Jianzhao; Larson, Timothy V; Sheppard, Lianne.
Affiliation
  • Kim SY; Department of Cancer AI and Digital Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA. Electronic address: sykim@ncc.re.kr.
  • Blanco MN; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.
  • Bi J; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.
  • Larson TV; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA; Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA.
  • Sheppard L; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA.
Environ Res ; 223: 115451, 2023 04 15.
Article in En | MEDLINE | ID: mdl-36764437
ABSTRACT

BACKGROUND:

Both exposure monitoring and exposure prediction have played key roles in assessing individual-level long-term exposure to air pollutants and their associations with human health. While there have been notable advances in exposure prediction methods, improvements in monitoring designs are also necessary, particularly given new monitoring paradigms leveraging low-cost sensors and mobile platforms.

OBJECTIVES:

We aim to provide a conceptual summary of novel monitoring designs for air pollution cohort studies that leverage new paradigms and technologies, to investigate their characteristics in real-world examples, and to offer practical guidance to future studies.

METHODS:

We propose a conceptual summary that focuses on two overarching types of monitoring designs, mobile and non-mobile, as well as their subtypes. We define mobile designs as monitoring from a moving platform, and non-mobile designs as stationary monitoring from permanent or temporary locations. We only consider non-mobile studies with cost-effective sampling devices. Then we discuss similarities and differences across previous studies with respect to spatial and temporal representation, data comparability between design classes, and the data leveraged for model development. Finally, we provide specific suggestions for future monitoring designs.

RESULTS:

Most mobile and non-mobile monitoring studies selected monitoring sites based on land use instead of residential locations, and deployed monitors over limited time periods. Some studies applied multiple design and/or sub-design classes to the same area, time period, or instrumentation, to allow comparison. Even fewer studies leveraged monitoring data from different designs to improve exposure assessment by capitalizing on different strengths. In order to maximize the benefit of new monitoring technologies, future studies should adopt monitoring designs that prioritize residence-based site selection with comprehensive temporal coverage and leverage data from different designs for model development in the presence of good data compatibility.

DISCUSSION:

Our conceptual overview provides practical guidance on novel exposure assessment monitoring for epidemiological applications.
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Full text: 1 Database: MEDLINE Main subject: Air Pollutants / Air Pollution Type of study: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies / Systematic_reviews Limits: Humans Language: En Journal: Environ Res Year: 2023 Type: Article

Full text: 1 Database: MEDLINE Main subject: Air Pollutants / Air Pollution Type of study: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies / Systematic_reviews Limits: Humans Language: En Journal: Environ Res Year: 2023 Type: Article