ArticleHealth & place2023
Accounting for space, time, and behavior using GPS derived dynamic measures of environmental exposure.
Article in Health & place, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Linking "Big" Geospatial and Health Data: Implications for Research in Environmental Epidemiology.Environmental health perspectives · 2026Article
- Environmental Exposure and Mental Health in Hong Kong: Protocol for a GPS- and Biosensor-Based Observational Study.JMIR research protocols · 2026Article
- Testing the efficacy and mechanisms of an SMS intervention focused on motivating peer network support to reduce alcohol consumption in non-collegiate young adults: Protocol for a randomized trial.Contemporary clinical trials · 2025Article
- Article
- Is home where the heat is? comparing residence-based with mobility-based measures of heat exposure in San Diego, California.Journal of exposure science & environmental epidemiology · 2025Article
- Changes in activity spaces, life spaces, and exposures to physical activity-promoting environments among women with overweight or obesity.Health & place · 2025Article
- Exposure to Fine Particulate Matter During Pregnancy Is Associated With Hippocampal Development in Offspring.Biological psychiatry global open science · 2025Article
- Semi-Automated Processing of Harmonized Accelerometer and GPS Data in R:Sensors (Basel, Switzerland) · 2025Article
- Combined impact of dynamic air pollution and transportation noise on cardiometabolic disorders in San Diego County.American journal of epidemiology · 2025Article
- A review of geospatial exposure models and approaches for health data integration.Journal of exposure science & environmental epidemiology · 2025Review
- Defining household exposure to the food environment: A comparison of measures based on residential area and activity space.PloS one · 2025Article
- GPS-derived environmental exposures during pregnancy and early postpartum - Evidence from the madres cohort.The Science of the total environment · 2024Article
- Measuring environmental exposures in people's activity space: The need to account for travel modes and exposure decay.Journal of exposure science & environmental epidemiology · 2023Article
- Aircraft and road traffic noise, insulin resistance, and diabetes: The role of neighborhood socioeconomic status in San Diego County.Environmental pollution (Barking, Essex : 1987) · 2023Article
- Comparison of static and dynamic exposures to air pollution, noise, and greenness among seniors living in compact-city environments.International journal of health geographics · 2023Article
- Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics.Environmental research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Time-weighted spatial averaging approaches (TWSA) are an increasingly utilized method for calculating exposure using global positioning system (GPS) mobility data for health-related research. They can provide a time-weighted measure of exposure, or dose, to various environments or health hazards. However, little work has been done to compare existing methodologies, nor to assess how sensitive these methods are to mobility data inputs (e.g., walking vs driving), the type of environmental data being assessed as the exposure (e.g., continuous surfaces vs points of interest), and underlying point-pattern clustering of participants (e.g., if a person is highly mobile vs predominantly stationary). Here we contrast three TWSA approaches that have been previously used or recently introduced in the literature: Kernel Density Estimation (KDE), Density Ranking (DR), and Point Overlay (PO). We feed GPS and accelerometer data from 602 participants through each method to derive time-weighted activity spaces, comparing four mobility behaviors: all movement, stationary time, walking time, and in-vehicle time. We then calculate exposure values derived from the various TWSA activity spaces with four environmental layer data types (point, line, area, surface). Similarities and differences across TWSA derived exposures for the sample and between individuals are explored, and we discuss interpretation of TWSA outputs providing recommendations for researchers seeking to apply these methods to health-related studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.