Cover Image
QR Code

Bring Your Own Location Data: Use of Google Smartphone Location History Data for Environmental Health Research.

BACKGROUND: Environmental exposures are commonly estimated using spatial methods, with most epidemiological studies relying on home addresses. Passively collected smartphone location data, like Google Location History (GLH) data, may present an opportunity to integrate existing long-term time–acti...

Full description

Published in:Environmental Health Perspectives Vol. 130; no. 11; pp. 117005-1 - 117014
Main Authors: Hystad, Perry, Amram, Ofer, Oje, Funso, Larkin, Andrew, Boakye, Kwadwo, Avery, Ally, Gebremedhin, Assefaw, Duncan, Glen
Format: pictorial research tables/charts Journal Article
Published: National Institute of Environmental Health Sciences Nov2022
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=160747202&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 160747202
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        00916765
        3B5
      jtl: Environmental Health Perspectives
      issn: 00916765
      maglogo: N
    pubinfo:
      dt: Nov2022
      vid: 130
      iid: 11
      pid: 56539
      pub: National Institute of Environmental Health Sciences
      place: Research Triangle Park, North Carolina
    artinfo:
      ui:
        160747202
        160747202
        160747202
        10.1289/EHP10829
        160747202
      ppf: 117005-1
      ppct: 9
      formats:
      tig:
        atl: Bring Your Own Location Data: Use of Google Smartphone Location History Data for Environmental Health Research.
      aug:
        au:
          Hystad, Perry
          Amram, Ofer
          Oje, Funso
          Larkin, Andrew
          Boakye, Kwadwo
          Avery, Ally
          Gebremedhin, Assefaw
          Duncan, Glen
        affil: College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon, USA
      sug:
        subj:
          Environmental Health
          Research
          Geographic Information Systems
          Web Search Engines
          Smartphone Utilization
          Human
          Male
          Female
          Adult
          Middle Age
          Retrospective Design
          Data Analysis Software
          Independent Variable
          T-Tests
          Descriptive Statistics
          Correlation Coefficient
          Global Positioning System
          Air Pollution
          Environmental Exposure
          Cost Benefit Analysis
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Male
          Female
      ab: BACKGROUND: Environmental exposures are commonly estimated using spatial methods, with most epidemiological studies relying on home addresses. Passively collected smartphone location data, like Google Location History (GLH) data, may present an opportunity to integrate existing long-term time–activity data. OBJECTIVES: We aimed to evaluate the potential use of GLH data for capturing long-term retrospective time–activity data for environmental health research. METHODS: We included 378 individuals who participated in previous Global Positioning System (GPS) studies within the Washington State Twin Registry. GLH data consists of location information that has been routinely collected since 2010 when location sharing was enabled within android operating systems or Google apps. We created instructions for participants to download their GLH data and provide it through secure data transfer. We summarized the GLH data provided, compared it to available GPS data, and conducted an exposure assessment for nitrogen dioxide (NO2) air pollution. RESULTS: Of 378 individuals contacted, we received GLH data from 61 individuals (16.1%) and 53 (14.0%) indicated interest but did not have historical GLH data available. The provided GLH data spanned 2010–2021 and included 34 million locations, capturing 66,677 participant days. The median number of days with GLH data per participant was 752, capturing 442 unique locations. When we compared GLH data to 2-wk GPS data (~1.8 million points), 95% of GPS time–activity points were within 100 m of GLH locations. We observed important differences between NO2 exposures assigned at home locations compared with GLH locations, highlighting the importance of GLH data to environmental exposure assessment. DISCUSSION: We believe collecting GLH data is a feasible and cost-effective method for capturing retrospective time–activity patterns for large populations that presents new opportunities for environmental epidemiology. Cohort studies should consider adding GLH data collection to capture historical time–activity patterns of participants, employing a “bring-your-own-location-data” citizen science approach. Privacy remains a concern that needs to be carefully managed when using GLH data.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N